diff --git a/autots/evaluator/auto_ts.py b/autots/evaluator/auto_ts.py
index dfe014d2..315c79bc 100644
--- a/autots/evaluator/auto_ts.py
+++ b/autots/evaluator/auto_ts.py
@@ -1548,6 +1548,11 @@ def fit(
         return self
 
     def validation_agg(self):
+        self.initial_results.model_results['Score'] = generate_score(
+            self.initial_results.model_results,
+            metric_weighting=self.metric_weighting,
+            prediction_interval=self.prediction_interval,
+        )
         self.validation_results = copy.copy(self.initial_results)
         self.validation_results = validation_aggregation(
             self.validation_results, df_train=self.df_wide_numeric
@@ -2194,11 +2199,19 @@ def export_template(
                         extra_mods.append(
                             export_template.nsmallest(1, columns=metric).copy()
                         )
+                        # and no ensemble version
+                        extra_mods.append(
+                            export_template[export_template['Ensemble'] == 0].nsmallest(1, columns=metric).copy()
+                        )
                 if max_metrics is not None:
                     for metric in max_metrics:
                         extra_mods.append(
                             export_template.nlargest(1, columns=metric).copy()
                         )
+                        # and no ensemble version
+                        extra_mods.append(
+                            export_template[export_template['Ensemble'] == 0].nlargest(1, columns=metric).copy()
+                        )
                 if str(max_per_model_class).isdigit():
                     export_template = (
                         export_template.sort_values('Score', ascending=True)
diff --git a/docs/build/doctrees/environment.pickle b/docs/build/doctrees/environment.pickle
index 1eb5b8c8..9dfa73e4 100644
Binary files a/docs/build/doctrees/environment.pickle and b/docs/build/doctrees/environment.pickle differ
diff --git a/docs/build/doctrees/index.doctree b/docs/build/doctrees/index.doctree
index 1dbbefc0..2948de85 100644
Binary files a/docs/build/doctrees/index.doctree and b/docs/build/doctrees/index.doctree differ
diff --git a/docs/build/doctrees/source/autots.datasets.doctree b/docs/build/doctrees/source/autots.datasets.doctree
index 8d3aa18a..79fd9864 100644
Binary files a/docs/build/doctrees/source/autots.datasets.doctree and b/docs/build/doctrees/source/autots.datasets.doctree differ
diff --git a/docs/build/doctrees/source/autots.doctree b/docs/build/doctrees/source/autots.doctree
index e6653b46..51866332 100644
Binary files a/docs/build/doctrees/source/autots.doctree and b/docs/build/doctrees/source/autots.doctree differ
diff --git a/docs/build/doctrees/source/autots.evaluator.doctree b/docs/build/doctrees/source/autots.evaluator.doctree
index 7703b17c..5a327165 100644
Binary files a/docs/build/doctrees/source/autots.evaluator.doctree and b/docs/build/doctrees/source/autots.evaluator.doctree differ
diff --git a/docs/build/doctrees/source/autots.models.doctree b/docs/build/doctrees/source/autots.models.doctree
index 8c5dadb1..d89b41c4 100644
Binary files a/docs/build/doctrees/source/autots.models.doctree and b/docs/build/doctrees/source/autots.models.doctree differ
diff --git a/docs/build/doctrees/source/autots.templates.doctree b/docs/build/doctrees/source/autots.templates.doctree
index 5e75b3f5..15065bb0 100644
Binary files a/docs/build/doctrees/source/autots.templates.doctree and b/docs/build/doctrees/source/autots.templates.doctree differ
diff --git a/docs/build/doctrees/source/autots.tools.doctree b/docs/build/doctrees/source/autots.tools.doctree
index 922af681..d7c799ce 100644
Binary files a/docs/build/doctrees/source/autots.tools.doctree and b/docs/build/doctrees/source/autots.tools.doctree differ
diff --git a/docs/build/doctrees/source/intro.doctree b/docs/build/doctrees/source/intro.doctree
index dec7f886..ca24dd76 100644
Binary files a/docs/build/doctrees/source/intro.doctree and b/docs/build/doctrees/source/intro.doctree differ
diff --git a/docs/build/doctrees/source/modules.doctree b/docs/build/doctrees/source/modules.doctree
index aeb9a21b..d34662db 100644
Binary files a/docs/build/doctrees/source/modules.doctree and b/docs/build/doctrees/source/modules.doctree differ
diff --git a/docs/build/doctrees/source/tutorial.doctree b/docs/build/doctrees/source/tutorial.doctree
index ed1a5943..45f17f12 100644
Binary files a/docs/build/doctrees/source/tutorial.doctree and b/docs/build/doctrees/source/tutorial.doctree differ
diff --git a/docs/build/html/.buildinfo b/docs/build/html/.buildinfo
index 75514961..4a6d98a6 100644
--- a/docs/build/html/.buildinfo
+++ b/docs/build/html/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 1f7b3cdc5940e728de375b92d31d88b6
+config: cd7239cc7dc0c2f0136aaa8bd24d37d1
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/docs/build/html/_static/basic.css b/docs/build/html/_static/basic.css
index 7577acb1..30fee9d0 100644
--- a/docs/build/html/_static/basic.css
+++ b/docs/build/html/_static/basic.css
@@ -237,6 +237,10 @@ a.headerlink {
     visibility: hidden;
 }
 
+a:visited {
+    color: #551A8B;
+}
+
 h1:hover > a.headerlink,
 h2:hover > a.headerlink,
 h3:hover > a.headerlink,
@@ -670,6 +674,16 @@ dd {
     margin-left: 30px;
 }
 
+.sig dd {
+    margin-top: 0px;
+    margin-bottom: 0px;
+}
+
+.sig dl {
+    margin-top: 0px;
+    margin-bottom: 0px;
+}
+
 dl > dd:last-child,
 dl > dd:last-child > :last-child {
     margin-bottom: 0;
@@ -738,6 +752,14 @@ abbr, acronym {
     cursor: help;
 }
 
+.translated {
+    background-color: rgba(207, 255, 207, 0.2)
+}
+
+.untranslated {
+    background-color: rgba(255, 207, 207, 0.2)
+}
+
 /* -- code displays --------------------------------------------------------- */
 
 pre {
diff --git a/docs/build/html/_static/documentation_options.js b/docs/build/html/_static/documentation_options.js
index f04691fd..7ce78999 100644
--- a/docs/build/html/_static/documentation_options.js
+++ b/docs/build/html/_static/documentation_options.js
@@ -1,5 +1,4 @@
-var DOCUMENTATION_OPTIONS = {
-    URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
+const DOCUMENTATION_OPTIONS = {
     VERSION: '0.6.10',
     LANGUAGE: 'en',
     COLLAPSE_INDEX: false,
diff --git a/docs/build/html/_static/searchtools.js b/docs/build/html/_static/searchtools.js
index 97d56a74..7918c3fa 100644
--- a/docs/build/html/_static/searchtools.js
+++ b/docs/build/html/_static/searchtools.js
@@ -57,12 +57,12 @@ const _removeChildren = (element) => {
 const _escapeRegExp = (string) =>
   string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string
 
-const _displayItem = (item, searchTerms) => {
+const _displayItem = (item, searchTerms, highlightTerms) => {
   const docBuilder = DOCUMENTATION_OPTIONS.BUILDER;
-  const docUrlRoot = DOCUMENTATION_OPTIONS.URL_ROOT;
   const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX;
   const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX;
   const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY;
+  const contentRoot = document.documentElement.dataset.content_root;
 
   const [docName, title, anchor, descr, score, _filename] = item;
 
@@ -75,20 +75,24 @@ const _displayItem = (item, searchTerms) => {
     if (dirname.match(/\/index\/$/))
       dirname = dirname.substring(0, dirname.length - 6);
     else if (dirname === "index/") dirname = "";
-    requestUrl = docUrlRoot + dirname;
+    requestUrl = contentRoot + dirname;
     linkUrl = requestUrl;
   } else {
     // normal html builders
-    requestUrl = docUrlRoot + docName + docFileSuffix;
+    requestUrl = contentRoot + docName + docFileSuffix;
     linkUrl = docName + docLinkSuffix;
   }
   let linkEl = listItem.appendChild(document.createElement("a"));
   linkEl.href = linkUrl + anchor;
   linkEl.dataset.score = score;
   linkEl.innerHTML = title;
-  if (descr)
+  if (descr) {
     listItem.appendChild(document.createElement("span")).innerHTML =
       " (" + descr + ")";
+    // highlight search terms in the description
+    if (SPHINX_HIGHLIGHT_ENABLED)  // set in sphinx_highlight.js
+      highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
+  }
   else if (showSearchSummary)
     fetch(requestUrl)
       .then((responseData) => responseData.text())
@@ -97,6 +101,9 @@ const _displayItem = (item, searchTerms) => {
           listItem.appendChild(
             Search.makeSearchSummary(data, searchTerms)
           );
+        // highlight search terms in the summary
+        if (SPHINX_HIGHLIGHT_ENABLED)  // set in sphinx_highlight.js
+          highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
       });
   Search.output.appendChild(listItem);
 };
@@ -115,14 +122,15 @@ const _finishSearch = (resultCount) => {
 const _displayNextItem = (
   results,
   resultCount,
-  searchTerms
+  searchTerms,
+  highlightTerms,
 ) => {
   // results left, load the summary and display it
   // this is intended to be dynamic (don't sub resultsCount)
   if (results.length) {
-    _displayItem(results.pop(), searchTerms);
+    _displayItem(results.pop(), searchTerms, highlightTerms);
     setTimeout(
-      () => _displayNextItem(results, resultCount, searchTerms),
+      () => _displayNextItem(results, resultCount, searchTerms, highlightTerms),
       5
     );
   }
@@ -360,7 +368,7 @@ const Search = {
     // console.info("search results:", Search.lastresults);
 
     // print the results
-    _displayNextItem(results, results.length, searchTerms);
+    _displayNextItem(results, results.length, searchTerms, highlightTerms);
   },
 
   /**
diff --git a/docs/build/html/_static/sphinx_highlight.js b/docs/build/html/_static/sphinx_highlight.js
index aae669d7..8a96c69a 100644
--- a/docs/build/html/_static/sphinx_highlight.js
+++ b/docs/build/html/_static/sphinx_highlight.js
@@ -29,14 +29,19 @@ const _highlight = (node, addItems, text, className) => {
       }
 
       span.appendChild(document.createTextNode(val.substr(pos, text.length)));
+      const rest = document.createTextNode(val.substr(pos + text.length));
       parent.insertBefore(
         span,
         parent.insertBefore(
-          document.createTextNode(val.substr(pos + text.length)),
+          rest,
           node.nextSibling
         )
       );
       node.nodeValue = val.substr(0, pos);
+      /* There may be more occurrences of search term in this node. So call this
+       * function recursively on the remaining fragment.
+       */
+      _highlight(rest, addItems, text, className);
 
       if (isInSVG) {
         const rect = document.createElementNS(
@@ -140,5 +145,10 @@ const SphinxHighlight = {
   },
 };
 
-_ready(SphinxHighlight.highlightSearchWords);
-_ready(SphinxHighlight.initEscapeListener);
+_ready(() => {
+  /* Do not call highlightSearchWords() when we are on the search page.
+   * It will highlight words from the *previous* search query.
+   */
+  if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords();
+  SphinxHighlight.initEscapeListener();
+});
diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html
index fac1e00e..f8d31de9 100644
--- a/docs/build/html/genindex.html
+++ b/docs/build/html/genindex.html
@@ -1,16 +1,24 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="./">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>Index &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="_static/alabaster.css" />
-    <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-    <script src="_static/doctools.js"></script>
-    <script src="_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="_static/alabaster.css?v=a4fa0645" />
+    <script src="_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="_static/doctools.js?v=888ff710"></script>
+    <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="#" />
     <link rel="search" title="Search" href="search.html" />
    
@@ -3305,21 +3313,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/index.html b/docs/build/html/index.html
index c0bf0f78..fa094eb8 100644
--- a/docs/build/html/index.html
+++ b/docs/build/html/index.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="./">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>AutoTS &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="_static/alabaster.css" />
-    <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-    <script src="_static/doctools.js"></script>
-    <script src="_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="_static/alabaster.css?v=a4fa0645" />
+    <script src="_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="_static/doctools.js?v=888ff710"></script>
+    <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
     <link rel="next" title="Intro" href="source/intro.html" />
@@ -32,10 +40,10 @@
           <div class="body" role="main">
             
   <section id="autots">
-<h1>AutoTS<a class="headerlink" href="#autots" title="Permalink to this heading">¶</a></h1>
+<h1>AutoTS<a class="headerlink" href="#autots" title="Link to this heading">¶</a></h1>
 <p><a class="reference internal" href="#autots">autots</a> is an automated time series forecasting package for Python.</p>
 <section id="installation">
-<h2>Installation<a class="headerlink" href="#installation" title="Permalink to this heading">¶</a></h2>
+<h2>Installation<a class="headerlink" href="#installation" title="Link to this heading">¶</a></h2>
 <div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>autots
 </pre></div>
 </div>
@@ -43,7 +51,7 @@ <h2>Installation<a class="headerlink" href="#installation" title="Permalink to t
 </section>
 </section>
 <section id="getting-started">
-<h1>Getting Started<a class="headerlink" href="#getting-started" title="Permalink to this heading">¶</a></h1>
+<h1>Getting Started<a class="headerlink" href="#getting-started" title="Link to this heading">¶</a></h1>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="source/intro.html">Intro</a></li>
@@ -71,7 +79,7 @@ <h1>Getting Started<a class="headerlink" href="#getting-started" title="Permalin
 </div>
 </section>
 <section id="modules-api">
-<h1>Modules API<a class="headerlink" href="#modules-api" title="Permalink to this heading">¶</a></h1>
+<h1>Modules API<a class="headerlink" href="#modules-api" title="Link to this heading">¶</a></h1>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="source/modules.html">autots</a><ul>
@@ -82,7 +90,7 @@ <h1>Modules API<a class="headerlink" href="#modules-api" title="Permalink to thi
 </div>
 </section>
 <section id="indices-and-tables">
-<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Permalink to this heading">¶</a></h1>
+<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Link to this heading">¶</a></h1>
 <ul class="simple">
 <li><p><a class="reference internal" href="genindex.html"><span class="std std-ref">Index</span></a></p></li>
 <li><p><a class="reference internal" href="py-modindex.html"><span class="std std-ref">Module Index</span></a></p></li>
@@ -172,21 +180,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/py-modindex.html b/docs/build/html/py-modindex.html
index b359b1fc..70621795 100644
--- a/docs/build/html/py-modindex.html
+++ b/docs/build/html/py-modindex.html
@@ -1,16 +1,24 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="./">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>Python Module Index &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="_static/alabaster.css" />
-    <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-    <script src="_static/doctools.js"></script>
-    <script src="_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="_static/alabaster.css?v=a4fa0645" />
+    <script src="_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="_static/doctools.js?v=888ff710"></script>
+    <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
 
@@ -384,21 +392,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/search.html b/docs/build/html/search.html
index 3df5ee7b..5174fc8f 100644
--- a/docs/build/html/search.html
+++ b/docs/build/html/search.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="./">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>Search &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="_static/alabaster.css" />
+    <link rel="stylesheet" type="text/css" href="_static/pygments.css?v=b76e3c8a" />
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autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.random_model"]], "regression_check (autots.evaluator.auto_ts.autots attribute)": [[3, "autots.evaluator.auto_ts.AutoTS.regression_check"]], "remove_leading_zeros() (in module autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.remove_leading_zeros"]], "results() (autots.evaluator.auto_ts.autots method)": [[3, "autots.evaluator.auto_ts.AutoTS.results"]], "retrieve_validation_forecasts() (autots.evaluator.auto_ts.autots method)": [[3, "autots.evaluator.auto_ts.AutoTS.retrieve_validation_forecasts"]], "rmse() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.rmse"]], "root_mean_square_error() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.root_mean_square_error"]], "rps() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.rps"]], "run() (autots.evaluator.benchmark.benchmark method)": [[3, "autots.evaluator.benchmark.Benchmark.run"]], "save() (autots.evaluator.auto_model.templateevalobject method)": [[3, "autots.evaluator.auto_model.TemplateEvalObject.save"]], "save_template() (autots.evaluator.auto_ts.autots method)": [[3, "autots.evaluator.auto_ts.AutoTS.save_template"]], "scaled_pinball_loss() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.scaled_pinball_loss"]], "score_per_series (autots.evaluator.auto_ts.autots attribute)": [[3, "autots.evaluator.auto_ts.AutoTS.score_per_series"]], "score_to_anomaly() (autots.evaluator.anomaly_detector.anomalydetector method)": [[3, "autots.evaluator.anomaly_detector.AnomalyDetector.score_to_anomaly"]], "set_limit() (autots.evaluator.event_forecasting.eventriskforecast method)": [[3, "autots.evaluator.event_forecasting.EventRiskForecast.set_limit"]], "set_limit() (autots.evaluator.event_forecasting.eventriskforecast static method)": [[3, "id13"]], "set_limit_forecast() (in module autots.evaluator.event_forecasting)": [[3, "autots.evaluator.event_forecasting.set_limit_forecast"]], "set_limit_forecast_historic() (in module autots.evaluator.event_forecasting)": [[3, "autots.evaluator.event_forecasting.set_limit_forecast_historic"]], "smape() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.smape"]], "smoothness() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.smoothness"]], "spl() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.spl"]], "symmetric_mean_absolute_percentage_error() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.symmetric_mean_absolute_percentage_error"]], "threshold_loss() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.threshold_loss"]], "trans_dict_recomb() (in module autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.trans_dict_recomb"]], "unpack_ensemble_models() (in module autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.unpack_ensemble_models"]], "unsorted_wasserstein() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.unsorted_wasserstein"]], "validate_num_validations() (in module autots.evaluator.validation)": [[3, "autots.evaluator.validation.validate_num_validations"]], "validation_agg() (autots.evaluator.auto_ts.autots method)": [[3, "autots.evaluator.auto_ts.AutoTS.validation_agg"]], "validation_aggregation() (in module autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.validation_aggregation"]], "wasserstein() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.wasserstein"]], "arch (class in autots.models.arch)": [[4, "autots.models.arch.ARCH"]], "ardl (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.ARDL"]], "arima (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.ARIMA"]], "averagevaluenaive (class in autots.models.basics)": [[4, "autots.models.basics.AverageValueNaive"]], "balltreemultivariatemotif (class in autots.models.basics)": [[4, "autots.models.basics.BallTreeMultivariateMotif"]], "bayesianmultioutputregression (class in autots.models.cassandra)": [[4, "autots.models.cassandra.BayesianMultiOutputRegression"]], "bestnensemble() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.BestNEnsemble"]], "cassandra (class in autots.models.cassandra)": [[4, "autots.models.cassandra.Cassandra"]], "componentanalysis (class in autots.models.sklearn)": [[4, "autots.models.sklearn.ComponentAnalysis"]], "constantnaive (class in autots.models.basics)": [[4, "autots.models.basics.ConstantNaive"]], "datepartregression (class in autots.models.sklearn)": [[4, "autots.models.sklearn.DatepartRegression"]], "distensemble() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.DistEnsemble"]], "dynamicfactor (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.DynamicFactor"]], "dynamicfactormq (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.DynamicFactorMQ"]], "ets (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.ETS"]], "ensembleforecast() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.EnsembleForecast"]], "ensembletemplategenerator() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.EnsembleTemplateGenerator"]], "fbprophet (class in autots.models.prophet)": [[4, "autots.models.prophet.FBProphet"]], "fft (class in autots.models.basics)": [[4, "autots.models.basics.FFT"]], "glm (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.GLM"]], "gls (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.GLS"]], "gluonts (class in autots.models.gluonts)": [[4, "autots.models.gluonts.GluonTS"]], "greykite (class in autots.models.greykite)": [[4, "autots.models.greykite.Greykite"]], "hdistensemble() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.HDistEnsemble"]], "horizontalensemble() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.HorizontalEnsemble"]], "horizontaltemplategenerator() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.HorizontalTemplateGenerator"]], "kalmanstatespace (class in autots.models.basics)": [[4, "autots.models.basics.KalmanStateSpace"]], "kerasrnn (class in autots.models.dnn)": [[4, "autots.models.dnn.KerasRNN"]], "latc (class in autots.models.matrix_var)": [[4, "autots.models.matrix_var.LATC"]], "lastvaluenaive (class in autots.models.basics)": [[4, "autots.models.basics.LastValueNaive"]], "mar (class in autots.models.matrix_var)": [[4, "autots.models.matrix_var.MAR"]], "mlensemble (class in autots.models.mlensemble)": [[4, "autots.models.mlensemble.MLEnsemble"]], "metricmotif (class in autots.models.basics)": [[4, "autots.models.basics.MetricMotif"]], "modelobject (class in autots.models.base)": [[4, "autots.models.base.ModelObject"]], "mosaicensemble() (in module autots.models.ensemble)": [[4, 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"module-autots.tools.fft"]], "autots.tools.hierarchial module": [[6, "module-autots.tools.hierarchial"]], "autots.tools.holiday module": [[6, "module-autots.tools.holiday"]], "autots.tools.impute module": [[6, "module-autots.tools.impute"]], "autots.tools.lunar module": [[6, "module-autots.tools.lunar"]], "autots.tools.percentile module": [[6, "module-autots.tools.percentile"]], "autots.tools.probabilistic module": [[6, "module-autots.tools.probabilistic"]], "autots.tools.profile module": [[6, "module-autots.tools.profile"]], "autots.tools.regressor module": [[6, "module-autots.tools.regressor"]], "autots.tools.seasonal module": [[6, "module-autots.tools.seasonal"]], "autots.tools.shaping module": [[6, "module-autots.tools.shaping"]], "autots.tools.thresholding module": [[6, "module-autots.tools.thresholding"]], "autots.tools.transform module": [[6, "module-autots.tools.transform"]], "autots.tools.window_functions module": [[6, "module-autots.tools.window_functions"]], "Intro": [[7, "intro"]], "Table of Contents": [[7, "table-of-contents"], [9, "table-of-contents"]], "Basic Use": [[7, "id2"]], "Tips for Speed and Large Data:": [[7, "id3"]], "How to Contribute:": [[7, "how-to-contribute"]], "autots": [[8, "autots"]], "Tutorial": [[9, "tutorial"]], "Extended Tutorial": [[9, "extended-tutorial"]], "A simple example": [[9, "id1"]], "Import of data": [[9, "import-of-data"]], "You can tailor the process in a few ways\u2026": [[9, "you-can-tailor-the-process-in-a-few-ways"]], "What to Worry About": [[9, "what-to-worry-about"]], "Validation and Cross Validation": [[9, "id2"]], "Another Example:": [[9, "id3"]], "Model Lists": [[9, "id4"]], "Deployment and Template Import/Export": [[9, "deployment-and-template-import-export"]], "Running Just One Model": [[9, "id5"]], "Metrics": [[9, "id6"]], "Hierarchial and Grouped Forecasts": [[9, "hierarchial-and-grouped-forecasts"]], "Ensembles": [[9, "id7"]], "Installation and Dependency Versioning": [[9, "installation-and-dependency-versioning"]], "Requirements:": [[9, "requirements"]], "Optional Packages": [[9, "optional-packages"]], "Safest bet for installation:": [[9, "safest-bet-for-installation"]], "Intel conda channel installation (sometime faster, also, more prone to bugs)": [[9, "intel-conda-channel-installation-sometime-faster-also-more-prone-to-bugs"]], "Speed Benchmark": [[9, "speed-benchmark"]], "Caveats and Advice": [[9, "caveats-and-advice"]], "Mysterious crashes": [[9, "mysterious-crashes"]], "Series IDs really need to be unique (or column names need to be all unique in wide data)": [[9, "series-ids-really-need-to-be-unique-or-column-names-need-to-be-all-unique-in-wide-data"]], "Short Training History": [[9, "short-training-history"]], "Adding regressors and other information": [[9, "adding-regressors-and-other-information"]], "Simulation Forecasting": [[9, "id8"]], "Event Risk Forecasting and Anomaly Detection": [[9, "event-risk-forecasting-and-anomaly-detection"]], "A Hack for Passing in Parameters (that aren\u2019t otherwise available)": [[9, "a-hack-for-passing-in-parameters-that-aren-t-otherwise-available"]], "Categorical Data": [[9, "categorical-data"]], "Custom and Unusual Frequencies": [[9, "custom-and-unusual-frequencies"]], "Using the Transformers independently": [[9, "using-the-transformers-independently"]], "Note on ~Regression Models": [[9, "note-on-regression-models"]], "Models": [[9, "id9"]]}, "indexentries": {"anomalydetector (class in autots)": [[1, "autots.AnomalyDetector"]], "autots (class in autots)": [[1, "autots.AutoTS"]], "cassandra (class in autots)": [[1, "autots.Cassandra"]], "eventriskforecast (class in autots)": [[1, "autots.EventRiskForecast"]], "generaltransformer (class in autots)": [[1, "autots.GeneralTransformer"]], "holidaydetector (class in autots)": [[1, "autots.HolidayDetector"]], "randomtransform() (in module autots)": [[1, "autots.RandomTransform"]], "transformts (in module autots)": [[1, "autots.TransformTS"]], "analyze_trend() (autots.cassandra method)": [[1, "autots.Cassandra.analyze_trend"]], "anomalies (autots.cassandra..anomaly_detector attribute)": [[1, "autots.Cassandra..anomaly_detector.anomalies"]], "auto_fit() (autots.cassandra method)": [[1, "autots.Cassandra.auto_fit"]], "autots": [[1, "module-autots"]], "back_forecast() (autots.autots method)": [[1, "autots.AutoTS.back_forecast"]], "base_scaler() (autots.cassandra method)": [[1, "autots.Cassandra.base_scaler"]], "best_model (autots.autots attribute)": [[1, "autots.AutoTS.best_model"]], "best_model_ensemble (autots.autots attribute)": [[1, "autots.AutoTS.best_model_ensemble"]], "best_model_name (autots.autots attribute)": [[1, "autots.AutoTS.best_model_name"]], "best_model_params (autots.autots attribute)": [[1, "autots.AutoTS.best_model_params"]], "best_model_per_series_mape() (autots.autots method)": [[1, "autots.AutoTS.best_model_per_series_mape"]], "best_model_per_series_score() (autots.autots method)": [[1, "autots.AutoTS.best_model_per_series_score"]], "best_model_transformation_params (autots.autots attribute)": [[1, "autots.AutoTS.best_model_transformation_params"]], "compare_actual_components() (autots.cassandra method)": [[1, "autots.Cassandra.compare_actual_components"]], "create_forecast_index() (autots.cassandra method)": [[1, "autots.Cassandra.create_forecast_index"]], "create_lagged_regressor() (in module autots)": [[1, "autots.create_lagged_regressor"]], "create_regressor() (in module autots)": [[1, "autots.create_regressor"]], "create_t() (autots.cassandra method)": [[1, "autots.Cassandra.create_t"]], "cross_validate() (autots.cassandra method)": [[1, "autots.Cassandra.cross_validate"]], "dates_to_holidays() (autots.cassandra.holiday_detector method)": [[1, "autots.Cassandra.holiday_detector.dates_to_holidays"]], "dates_to_holidays() (autots.holidaydetector method)": [[1, "autots.HolidayDetector.dates_to_holidays"]], "detect() (autots.anomalydetector method)": [[1, "autots.AnomalyDetector.detect"]], "detect() (autots.holidaydetector method)": [[1, "autots.HolidayDetector.detect"]], "df_wide_numeric (autots.autots attribute)": [[1, "autots.AutoTS.df_wide_numeric"]], "diagnose_params() (autots.autots method)": [[1, "autots.AutoTS.diagnose_params"]], "expand_horizontal() (autots.autots method)": [[1, "autots.AutoTS.expand_horizontal"]], "export_best_model() (autots.autots method)": [[1, "autots.AutoTS.export_best_model"]], "export_template() (autots.autots method)": [[1, "autots.AutoTS.export_template"]], "failure_rate() (autots.autots method)": [[1, "autots.AutoTS.failure_rate"]], "feature_importance() (autots.cassandra method)": [[1, "autots.Cassandra.feature_importance"]], "fill_na() (autots.generaltransformer method)": [[1, "autots.GeneralTransformer.fill_na"]], "fit() (autots.anomalydetector method)": [[1, "autots.AnomalyDetector.fit"]], "fit() (autots.autots method)": [[1, "autots.AutoTS.fit"]], "fit() (autots.cassandra method)": [[1, "autots.Cassandra.fit"], [1, "id0"]], "fit() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.fit"], [1, "id9"]], "fit() (autots.generaltransformer method)": [[1, "autots.GeneralTransformer.fit"]], "fit() (autots.holidaydetector method)": [[1, "autots.HolidayDetector.fit"]], "fit_anomaly_classifier() (autots.anomalydetector method)": [[1, "autots.AnomalyDetector.fit_anomaly_classifier"]], "fit_data() (autots.autots method)": [[1, "autots.AutoTS.fit_data"]], "fit_data() (autots.cassandra method)": [[1, "autots.Cassandra.fit_data"]], "fit_transform() (autots.generaltransformer method)": [[1, "autots.GeneralTransformer.fit_transform"]], "generate_historic_risk_array() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.generate_historic_risk_array"]], "generate_historic_risk_array() (autots.eventriskforecast static method)": [[1, "id10"]], "generate_result_windows() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.generate_result_windows"], [1, "id11"]], "generate_risk_array() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.generate_risk_array"]], "generate_risk_array() (autots.eventriskforecast static method)": [[1, "id12"]], "get_metric_corr() (autots.autots method)": [[1, "autots.AutoTS.get_metric_corr"]], "get_new_params() (autots.anomalydetector static method)": [[1, "autots.AnomalyDetector.get_new_params"]], "get_new_params() (autots.autots static method)": [[1, "autots.AutoTS.get_new_params"]], "get_new_params() (autots.cassandra method)": [[1, "autots.Cassandra.get_new_params"], [1, "id1"]], "get_new_params() (autots.generaltransformer static method)": [[1, "autots.GeneralTransformer.get_new_params"]], "get_new_params() (autots.holidaydetector static method)": [[1, "autots.HolidayDetector.get_new_params"]], "get_params() (autots.cassandra method)": [[1, "autots.Cassandra.get_params"]], "holiday_count (autots.cassandra. attribute)": [[1, "autots.Cassandra..holiday_count"]], "holidays (autots.cassandra. attribute)": [[1, "autots.Cassandra..holidays"]], "horizontal_per_generation() (autots.autots method)": [[1, "autots.AutoTS.horizontal_per_generation"]], "horizontal_to_df() (autots.autots method)": [[1, "autots.AutoTS.horizontal_to_df"]], "import_best_model() (autots.autots method)": [[1, "autots.AutoTS.import_best_model"]], "import_results() (autots.autots method)": [[1, "autots.AutoTS.import_results"]], "import_template() (autots.autots method)": [[1, "autots.AutoTS.import_template"]], "infer_frequency() (in module autots)": [[1, "autots.infer_frequency"]], "inverse_transform() (autots.generaltransformer method)": [[1, "autots.GeneralTransformer.inverse_transform"]], "list_failed_model_types() (autots.autots method)": [[1, "autots.AutoTS.list_failed_model_types"]], "load_artificial() (in module autots)": [[1, "autots.load_artificial"]], "load_daily() (in module autots)": [[1, "autots.load_daily"]], "load_hourly() (in module autots)": [[1, "autots.load_hourly"]], "load_linear() (in module autots)": [[1, "autots.load_linear"]], "load_live_daily() (in module autots)": [[1, "autots.load_live_daily"]], "load_monthly() (in module autots)": [[1, "autots.load_monthly"]], "load_sine() (in module autots)": [[1, "autots.load_sine"]], "load_template() (autots.autots method)": [[1, "autots.AutoTS.load_template"]], "load_weekdays() (in module autots)": [[1, "autots.load_weekdays"]], "load_weekly() (in module autots)": [[1, "autots.load_weekly"]], "load_yearly() (in module autots)": [[1, "autots.load_yearly"]], "long_to_wide() (in module autots)": [[1, "autots.long_to_wide"]], "model_forecast() (in module autots)": [[1, "autots.model_forecast"]], "model_results (autots.autots.initial_results attribute)": [[1, "autots.AutoTS.initial_results.model_results"]], "module": [[1, "module-autots"], [2, "module-autots.datasets"], [2, "module-autots.datasets.fred"], [3, "module-autots.evaluator"], [3, 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"module-autots.models.tide"], [5, "module-autots.templates"], [5, "module-autots.templates.general"], [6, "module-autots.tools"], [6, "module-autots.tools.anomaly_utils"], [6, "module-autots.tools.calendar"], [6, "module-autots.tools.cointegration"], [6, "module-autots.tools.cpu_count"], [6, "module-autots.tools.fast_kalman"], [6, "module-autots.tools.fft"], [6, "module-autots.tools.hierarchial"], [6, "module-autots.tools.holiday"], [6, "module-autots.tools.impute"], [6, "module-autots.tools.lunar"], [6, "module-autots.tools.percentile"], [6, "module-autots.tools.probabilistic"], [6, "module-autots.tools.profile"], [6, "module-autots.tools.regressor"], [6, "module-autots.tools.seasonal"], [6, "module-autots.tools.shaping"], [6, "module-autots.tools.thresholding"], [6, "module-autots.tools.transform"], [6, "module-autots.tools.window_functions"]], "mosaic_to_df() (autots.autots method)": [[1, "autots.AutoTS.mosaic_to_df"]], "next_fit() (autots.cassandra method)": [[1, "autots.Cassandra.next_fit"]], "params (autots.cassandra. attribute)": [[1, "autots.Cassandra..params"]], "parse_best_model() (autots.autots method)": [[1, "autots.AutoTS.parse_best_model"]], "plot() (autots.anomalydetector method)": [[1, "autots.AnomalyDetector.plot"]], "plot() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.plot"], [1, "id13"]], "plot() (autots.holidaydetector method)": [[1, "autots.HolidayDetector.plot"]], "plot_anomaly() (autots.holidaydetector method)": [[1, "autots.HolidayDetector.plot_anomaly"]], "plot_back_forecast() (autots.autots method)": [[1, "autots.AutoTS.plot_back_forecast"]], "plot_backforecast() (autots.autots method)": [[1, "autots.AutoTS.plot_backforecast"]], "plot_components() (autots.cassandra method)": [[1, "autots.Cassandra.plot_components"], [1, "id2"]], "plot_eval() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.plot_eval"]], "plot_forecast() (autots.cassandra method)": [[1, "autots.Cassandra.plot_forecast"], [1, "id3"]], "plot_generation_loss() (autots.autots method)": [[1, "autots.AutoTS.plot_generation_loss"]], "plot_horizontal() (autots.autots method)": [[1, "autots.AutoTS.plot_horizontal"]], "plot_horizontal_model_count() (autots.autots method)": [[1, "autots.AutoTS.plot_horizontal_model_count"]], "plot_horizontal_per_generation() (autots.autots method)": [[1, "autots.AutoTS.plot_horizontal_per_generation"]], "plot_horizontal_transformers() (autots.autots method)": [[1, "autots.AutoTS.plot_horizontal_transformers"]], "plot_metric_corr() (autots.autots method)": [[1, "autots.AutoTS.plot_metric_corr"]], "plot_per_series_error() (autots.autots method)": [[1, "autots.AutoTS.plot_per_series_error"]], "plot_per_series_mape() (autots.autots method)": [[1, "autots.AutoTS.plot_per_series_mape"]], "plot_per_series_smape() (autots.autots method)": [[1, "autots.AutoTS.plot_per_series_smape"]], "plot_things() (autots.cassandra method)": [[1, "autots.Cassandra.plot_things"]], "plot_transformer_failure_rate() (autots.autots method)": [[1, "autots.AutoTS.plot_transformer_failure_rate"]], "plot_trend() (autots.cassandra method)": [[1, "autots.Cassandra.plot_trend"], [1, "id4"]], "plot_validations() (autots.autots method)": [[1, "autots.AutoTS.plot_validations"]], "predict() (autots.autots method)": [[1, "autots.AutoTS.predict"]], "predict() (autots.cassandra method)": [[1, "autots.Cassandra.predict"], [1, "id5"]], "predict() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.predict"], [1, "id14"]], "predict_historic() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.predict_historic"], [1, "id15"]], "predict_new_product() (autots.cassandra method)": [[1, "autots.Cassandra.predict_new_product"]], "predict_x_array (autots.cassandra. attribute)": [[1, "autots.Cassandra..predict_x_array"]], "predicted_trend (autots.cassandra. attribute)": [[1, "autots.Cassandra..predicted_trend"]], "process_components() (autots.cassandra method)": [[1, "autots.Cassandra.process_components"]], "regression_check (autots.autots attribute)": [[1, "autots.AutoTS.regression_check"]], "results() (autots.autots method)": [[1, "autots.AutoTS.results"]], "retrieve_transformer() (autots.generaltransformer class method)": [[1, "autots.GeneralTransformer.retrieve_transformer"]], "retrieve_validation_forecasts() (autots.autots method)": [[1, "autots.AutoTS.retrieve_validation_forecasts"]], "return_components() (autots.cassandra method)": [[1, "autots.Cassandra.return_components"], [1, "id6"]], "rolling_trend() (autots.cassandra method)": [[1, "autots.Cassandra.rolling_trend"]], "save_template() (autots.autots method)": [[1, "autots.AutoTS.save_template"]], "scale_data() (autots.cassandra method)": [[1, "autots.Cassandra.scale_data"]], "score_per_series (autots.autots attribute)": [[1, "autots.AutoTS.score_per_series"]], "score_to_anomaly() (autots.anomalydetector method)": [[1, "autots.AnomalyDetector.score_to_anomaly"]], "scores (autots.cassandra..anomaly_detector attribute)": [[1, "autots.Cassandra..anomaly_detector.scores"]], "set_limit() (autots.eventriskforecast method)": [[1, "autots.EventRiskForecast.set_limit"]], "set_limit() (autots.eventriskforecast static method)": [[1, "id16"]], "to_origin_space() (autots.cassandra method)": [[1, "autots.Cassandra.to_origin_space"]], "transform() (autots.generaltransformer method)": [[1, "autots.GeneralTransformer.transform"]], "treatment_causal_impact() (autots.cassandra method)": [[1, "autots.Cassandra.treatment_causal_impact"]], "trend_train (autots.cassandra. attribute)": [[1, "autots.Cassandra..trend_train"]], "validation_agg() (autots.autots method)": [[1, "autots.AutoTS.validation_agg"]], "x_array (autots.cassandra. attribute)": [[1, "autots.Cassandra..x_array"]], "autots.datasets": [[2, "module-autots.datasets"]], "autots.datasets.fred": [[2, "module-autots.datasets.fred"]], "get_fred_data() (in module autots.datasets.fred)": [[2, "autots.datasets.fred.get_fred_data"]], "load_artificial() (in module autots.datasets)": [[2, "autots.datasets.load_artificial"]], "load_daily() (in module autots.datasets)": [[2, "autots.datasets.load_daily"]], "load_hourly() (in module autots.datasets)": [[2, "autots.datasets.load_hourly"]], "load_linear() (in module autots.datasets)": [[2, "autots.datasets.load_linear"]], "load_live_daily() (in module autots.datasets)": [[2, "autots.datasets.load_live_daily"]], "load_monthly() (in module autots.datasets)": [[2, "autots.datasets.load_monthly"]], "load_sine() (in module autots.datasets)": [[2, "autots.datasets.load_sine"]], "load_weekdays() (in module autots.datasets)": [[2, "autots.datasets.load_weekdays"]], "load_weekly() (in module autots.datasets)": [[2, "autots.datasets.load_weekly"]], "load_yearly() (in module autots.datasets)": [[2, "autots.datasets.load_yearly"]], "load_zeroes() (in module autots.datasets)": [[2, "autots.datasets.load_zeroes"]], "anomalydetector (class in autots.evaluator.anomaly_detector)": [[3, "autots.evaluator.anomaly_detector.AnomalyDetector"]], "autots (class in autots.evaluator.auto_ts)": [[3, "autots.evaluator.auto_ts.AutoTS"]], "benchmark (class in autots.evaluator.benchmark)": [[3, "autots.evaluator.benchmark.Benchmark"]], "eventriskforecast (class in autots.evaluator.event_forecasting)": [[3, "autots.evaluator.event_forecasting.EventRiskForecast"]], "holidaydetector (class in autots.evaluator.anomaly_detector)": [[3, "autots.evaluator.anomaly_detector.HolidayDetector"]], "modelmonster() (in module autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.ModelMonster"]], "modelprediction (class in autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.ModelPrediction"]], "newgenetictemplate() (in module autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.NewGeneticTemplate"]], "randomtemplate() (in module autots.evaluator.auto_model)": [[3, 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"unsorted_wasserstein() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.unsorted_wasserstein"]], "validate_num_validations() (in module autots.evaluator.validation)": [[3, "autots.evaluator.validation.validate_num_validations"]], "validation_agg() (autots.evaluator.auto_ts.autots method)": [[3, "autots.evaluator.auto_ts.AutoTS.validation_agg"]], "validation_aggregation() (in module autots.evaluator.auto_model)": [[3, "autots.evaluator.auto_model.validation_aggregation"]], "wasserstein() (in module autots.evaluator.metrics)": [[3, "autots.evaluator.metrics.wasserstein"]], "arch (class in autots.models.arch)": [[4, "autots.models.arch.ARCH"]], "ardl (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.ARDL"]], "arima (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.ARIMA"]], "averagevaluenaive (class in autots.models.basics)": [[4, "autots.models.basics.AverageValueNaive"]], "balltreemultivariatemotif (class in autots.models.basics)": [[4, "autots.models.basics.BallTreeMultivariateMotif"]], "bayesianmultioutputregression (class in autots.models.cassandra)": [[4, "autots.models.cassandra.BayesianMultiOutputRegression"]], "bestnensemble() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.BestNEnsemble"]], "cassandra (class in autots.models.cassandra)": [[4, "autots.models.cassandra.Cassandra"]], "componentanalysis (class in autots.models.sklearn)": [[4, "autots.models.sklearn.ComponentAnalysis"]], "constantnaive (class in autots.models.basics)": [[4, "autots.models.basics.ConstantNaive"]], "datepartregression (class in autots.models.sklearn)": [[4, "autots.models.sklearn.DatepartRegression"]], "distensemble() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.DistEnsemble"]], "dynamicfactor (class in autots.models.statsmodels)": [[4, "autots.models.statsmodels.DynamicFactor"]], "dynamicfactormq (class in autots.models.statsmodels)": [[4, 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autots.models.ensemble)": [[4, "autots.models.ensemble.HorizontalEnsemble"]], "horizontaltemplategenerator() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.HorizontalTemplateGenerator"]], "kalmanstatespace (class in autots.models.basics)": [[4, "autots.models.basics.KalmanStateSpace"]], "kerasrnn (class in autots.models.dnn)": [[4, "autots.models.dnn.KerasRNN"]], "latc (class in autots.models.matrix_var)": [[4, "autots.models.matrix_var.LATC"]], "lastvaluenaive (class in autots.models.basics)": [[4, "autots.models.basics.LastValueNaive"]], "mar (class in autots.models.matrix_var)": [[4, "autots.models.matrix_var.MAR"]], "mlensemble (class in autots.models.mlensemble)": [[4, "autots.models.mlensemble.MLEnsemble"]], "metricmotif (class in autots.models.basics)": [[4, "autots.models.basics.MetricMotif"]], "modelobject (class in autots.models.base)": [[4, "autots.models.base.ModelObject"]], "mosaicensemble() (in module autots.models.ensemble)": [[4, 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[[4, "autots.models.sklearn.DatepartRegression.fit_data"]], "fit_data() (autots.models.sklearn.multivariateregression method)": [[4, "autots.models.sklearn.MultivariateRegression.fit_data"]], "fit_data() (autots.models.sklearn.preprocessingregression method)": [[4, "autots.models.sklearn.PreprocessingRegression.fit_data"]], "fit_data() (autots.models.sklearn.windowregression method)": [[4, "autots.models.sklearn.WindowRegression.fit_data"]], "fit_linear_model() (in module autots.models.cassandra)": [[4, "autots.models.cassandra.fit_linear_model"]], "forecast (autots.models.base.predictionobject attribute)": [[4, "autots.models.base.PredictionObject.forecast"]], "generalize_horizontal() (in module autots.models.ensemble)": [[4, "autots.models.ensemble.generalize_horizontal"]], "generate_psi() (in module autots.models.matrix_var)": [[4, "autots.models.matrix_var.generate_Psi"]], "generate_classifier_params() (in module autots.models.sklearn)": [[4, 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autots.tools.transform)": [[6, "autots.tools.transform.random_cleaners"]], "random_datepart() (in module autots.tools.seasonal)": [[6, "autots.tools.seasonal.random_datepart"]], "random_state_space() (in module autots.tools.fast_kalman)": [[6, "autots.tools.fast_kalman.random_state_space"]], "reconcile() (autots.tools.hierarchial.hierarchial method)": [[6, "autots.tools.hierarchial.hierarchial.reconcile"]], "remove_outliers() (in module autots.tools.transform)": [[6, "autots.tools.transform.remove_outliers"]], "retrieve_closest_indices() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.retrieve_closest_indices"]], "retrieve_transformer() (autots.tools.transform.generaltransformer class method)": [[6, "autots.tools.transform.GeneralTransformer.retrieve_transformer"]], "rolling_mean() (in module autots.tools.impute)": [[6, "autots.tools.impute.rolling_mean"]], "rolling_window_view() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.rolling_window_view"]], "score_anomalies() (autots.tools.thresholding.nonparametricthreshold method)": [[6, "autots.tools.thresholding.NonparametricThreshold.score_anomalies"]], "score_to_anomaly() (autots.tools.transform.anomalyremoval method)": [[6, "autots.tools.transform.AnomalyRemoval.score_to_anomaly"]], "seasonal_independent_match() (in module autots.tools.seasonal)": [[6, "autots.tools.seasonal.seasonal_independent_match"]], "seasonal_int() (in module autots.tools.seasonal)": [[6, "autots.tools.seasonal.seasonal_int"]], "seasonal_window_match() (in module autots.tools.seasonal)": [[6, "autots.tools.seasonal.seasonal_window_match"]], "set_n_jobs() (in module autots.tools.cpu_count)": [[6, "autots.tools.cpu_count.set_n_jobs"]], "simple_context_slicer() (in module autots.tools.transform)": [[6, "autots.tools.transform.simple_context_slicer"]], "simple_train_test_split() (in module autots.tools.shaping)": [[6, "autots.tools.shaping.simple_train_test_split"]], "sk_outliers() (in module autots.tools.anomaly_utils)": [[6, "autots.tools.anomaly_utils.sk_outliers"]], "sliding_window_view() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.sliding_window_view"]], "smooth() (autots.tools.fast_kalman.kalmanfilter method)": [[6, "autots.tools.fast_kalman.KalmanFilter.smooth"]], "smooth() (in module autots.tools.fast_kalman)": [[6, "autots.tools.fast_kalman.smooth"]], "smooth_current() (autots.tools.fast_kalman.kalmanfilter method)": [[6, "autots.tools.fast_kalman.KalmanFilter.smooth_current"]], "split_digits_and_non_digits() (in module autots.tools.shaping)": [[6, "autots.tools.shaping.split_digits_and_non_digits"]], "subset_series() (in module autots.tools.shaping)": [[6, "autots.tools.shaping.subset_series"]], "to_jd() (in module autots.tools.calendar)": [[6, "autots.tools.calendar.to_jd"]], "todeg() (in module autots.tools.lunar)": [[6, "autots.tools.lunar.todeg"]], "torad() (in module autots.tools.lunar)": [[6, "autots.tools.lunar.torad"]], "transform() (autots.tools.hierarchial.hierarchial method)": [[6, "autots.tools.hierarchial.hierarchial.transform"]], "transform() (autots.tools.shaping.numerictransformer method)": [[6, "autots.tools.shaping.NumericTransformer.transform"]], "transform() (autots.tools.transform.alignlastdiff method)": [[6, "autots.tools.transform.AlignLastDiff.transform"]], "transform() (autots.tools.transform.alignlastvalue method)": [[6, "autots.tools.transform.AlignLastValue.transform"]], "transform() (autots.tools.transform.anomalyremoval method)": [[6, "autots.tools.transform.AnomalyRemoval.transform"]], "transform() (autots.tools.transform.bkbandpassfilter method)": [[6, "autots.tools.transform.BKBandpassFilter.transform"]], "transform() (autots.tools.transform.btcd method)": [[6, "autots.tools.transform.BTCD.transform"]], "transform() (autots.tools.transform.centerlastvalue method)": [[6, 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"autots.tools.transform.DifferencedTransformer.transform"]], "transform() (autots.tools.transform.discretize method)": [[6, "autots.tools.transform.Discretize.transform"]], "transform() (autots.tools.transform.ewmafilter method)": [[6, "autots.tools.transform.EWMAFilter.transform"]], "transform() (autots.tools.transform.emptytransformer method)": [[6, "autots.tools.transform.EmptyTransformer.transform"]], "transform() (autots.tools.transform.fftdecomposition method)": [[6, "autots.tools.transform.FFTDecomposition.transform"]], "transform() (autots.tools.transform.fftfilter method)": [[6, "autots.tools.transform.FFTFilter.transform"]], "transform() (autots.tools.transform.fastica method)": [[6, "autots.tools.transform.FastICA.transform"]], "transform() (autots.tools.transform.generaltransformer method)": [[6, "autots.tools.transform.GeneralTransformer.transform"]], "transform() (autots.tools.transform.hpfilter method)": [[6, "autots.tools.transform.HPFilter.transform"]], "transform() (autots.tools.transform.historicvalues method)": [[6, "autots.tools.transform.HistoricValues.transform"]], "transform() (autots.tools.transform.holidaytransformer method)": [[6, "autots.tools.transform.HolidayTransformer.transform"]], "transform() (autots.tools.transform.intermittentoccurrence method)": [[6, "autots.tools.transform.IntermittentOccurrence.transform"]], "transform() (autots.tools.transform.kalmansmoothing method)": [[6, "autots.tools.transform.KalmanSmoothing.transform"]], "transform() (autots.tools.transform.levelshiftmagic method)": [[6, "autots.tools.transform.LevelShiftMagic.transform"]], "transform() (autots.tools.transform.locallineartrend method)": [[6, "autots.tools.transform.LocalLinearTrend.transform"]], "transform() (autots.tools.transform.meandifference method)": [[6, "autots.tools.transform.MeanDifference.transform"]], "transform() (autots.tools.transform.pca method)": [[6, "autots.tools.transform.PCA.transform"]], "transform() (autots.tools.transform.pctchangetransformer method)": [[6, "autots.tools.transform.PctChangeTransformer.transform"]], "transform() (autots.tools.transform.positiveshift method)": [[6, "autots.tools.transform.PositiveShift.transform"]], "transform() (autots.tools.transform.regressionfilter method)": [[6, "autots.tools.transform.RegressionFilter.transform"]], "transform() (autots.tools.transform.replaceconstant method)": [[6, "autots.tools.transform.ReplaceConstant.transform"]], "transform() (autots.tools.transform.rollingmeantransformer method)": [[6, "autots.tools.transform.RollingMeanTransformer.transform"]], "transform() (autots.tools.transform.round method)": [[6, "autots.tools.transform.Round.transform"]], "transform() (autots.tools.transform.stlfilter method)": [[6, "autots.tools.transform.STLFilter.transform"]], "transform() (autots.tools.transform.scipyfilter method)": [[6, "autots.tools.transform.ScipyFilter.transform"]], "transform() (autots.tools.transform.seasonaldifference method)": [[6, "autots.tools.transform.SeasonalDifference.transform"]], "transform() (autots.tools.transform.sintrend method)": [[6, "autots.tools.transform.SinTrend.transform"]], "transform() (autots.tools.transform.slice method)": [[6, "autots.tools.transform.Slice.transform"]], "transform() (autots.tools.transform.statsmodelsfilter method)": [[6, "autots.tools.transform.StatsmodelsFilter.transform"]], "transformer_list_to_dict() (in module autots.tools.transform)": [[6, "autots.tools.transform.transformer_list_to_dict"]], "trimmed_mean() (in module autots.tools.percentile)": [[6, "autots.tools.percentile.trimmed_mean"]], "unvectorize_state() (autots.tools.fast_kalman.gaussian method)": [[6, "autots.tools.fast_kalman.Gaussian.unvectorize_state"]], "unvectorize_vars() (autots.tools.fast_kalman.gaussian method)": [[6, "autots.tools.fast_kalman.Gaussian.unvectorize_vars"]], "update() (autots.tools.fast_kalman.kalmanfilter method)": [[6, "autots.tools.fast_kalman.KalmanFilter.update"]], "update() (in module autots.tools.fast_kalman)": [[6, "autots.tools.fast_kalman.update"]], "update_with_nan_check() (in module autots.tools.fast_kalman)": [[6, "autots.tools.fast_kalman.update_with_nan_check"]], "values_to_anomalies() (in module autots.tools.anomaly_utils)": [[6, "autots.tools.anomaly_utils.values_to_anomalies"]], "wide_to_3d() (in module autots.tools.shaping)": [[6, "autots.tools.shaping.wide_to_3d"]], "window_id_maker() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_id_maker"]], "window_lin_reg() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_lin_reg"]], "window_lin_reg_mean() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_lin_reg_mean"]], "window_lin_reg_mean_no_nan() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_lin_reg_mean_no_nan"]], "window_maker() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_maker"]], "window_maker_2() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_maker_2"]], "window_maker_3() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_maker_3"]], "window_sum_mean() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_sum_mean"]], "window_sum_mean_nan_tail() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_sum_mean_nan_tail"]], "window_sum_nan_mean() (in module autots.tools.window_functions)": [[6, "autots.tools.window_functions.window_sum_nan_mean"]], "zscore_survival_function() (in module autots.tools.anomaly_utils)": [[6, "autots.tools.anomaly_utils.zscore_survival_function"]]}})
\ No newline at end of file
diff --git a/docs/build/html/source/autots.datasets.html b/docs/build/html/source/autots.datasets.html
index f19983ca..baf4f2bd 100644
--- a/docs/build/html/source/autots.datasets.html
+++ b/docs/build/html/source/autots.datasets.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="../">
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     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
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+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
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+    
     <title>autots.datasets package &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
-    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/doctools.js"></script>
-    <script src="../_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css?v=a4fa0645" />
+    <script src="../_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="../_static/doctools.js?v=888ff710"></script>
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     <link rel="index" title="Index" href="../genindex.html" />
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     <link rel="next" title="autots.evaluator package" href="autots.evaluator.html" />
@@ -33,18 +41,18 @@
           <div class="body" role="main">
             
   <section id="autots-datasets-package">
-<h1>autots.datasets package<a class="headerlink" href="#autots-datasets-package" title="Permalink to this heading">¶</a></h1>
+<h1>autots.datasets package<a class="headerlink" href="#autots-datasets-package" title="Link to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading">¶</a></h2>
 </section>
 <section id="module-autots.datasets.fred">
-<span id="autots-datasets-fred-module"></span><h2>autots.datasets.fred module<a class="headerlink" href="#module-autots.datasets.fred" title="Permalink to this heading">¶</a></h2>
+<span id="autots-datasets-fred-module"></span><h2>autots.datasets.fred module<a class="headerlink" href="#module-autots.datasets.fred" title="Link to this heading">¶</a></h2>
 <p>FRED (Federal Reserve Economic Data) Data Import</p>
 <p>requires API key from FRED
 and pip install fredapi</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.fred.get_fred_data">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.fred.</span></span><span class="sig-name descname"><span class="pre">get_fred_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fredkey</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">SeriesNameDict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_start</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sleep_seconds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.fred.get_fred_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.fred.</span></span><span class="sig-name descname"><span class="pre">get_fred_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fredkey</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">SeriesNameDict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_start</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sleep_seconds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.fred.get_fred_data" title="Link to this definition">¶</a></dt>
 <dd><p>Imports Data from Federal Reserve.
 For simplest results, make sure requested series are all of the same frequency.</p>
 <dl class="field-list simple">
@@ -64,11 +72,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.datasets">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.datasets" title="Permalink to this heading">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.datasets" title="Link to this heading">¶</a></h2>
 <p>Tools for Importing Sample Data</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_artificial">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_artificial</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_start</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_end</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_artificial" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_artificial</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_start</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_end</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_artificial" title="Link to this definition">¶</a></dt>
 <dd><p>Load artifically generated series from random distributions.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -83,7 +91,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_daily">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_daily</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_daily" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_daily</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_daily" title="Link to this definition">¶</a></dt>
 <dd><p>Daily sample data.</p>
 <dl class="simple">
 <dt>wiki = [</dt><dd><p>“Germany”, “Thanksgiving”, ‘all’, ‘Microsoft’,
@@ -106,13 +114,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_hourly">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_hourly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_hourly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_hourly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_hourly" title="Link to this definition">¶</a></dt>
 <dd><p>Traffic data from the MN DOT via the UCI data repository.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_linear">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_linear</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_random</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_linear" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_linear</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_random</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_linear" title="Link to this definition">¶</a></dt>
 <dd><p>Create a dataset of just zeroes for testing edge case.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -130,7 +138,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_live_daily">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_live_daily</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_start</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_end</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fred_key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fred_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['DGS10',</span> <span class="pre">'T5YIE',</span> <span class="pre">'SP500',</span> <span class="pre">'DCOILWTICO',</span> <span class="pre">'DEXUSEU',</span> <span class="pre">'WPU0911']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tickers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['MSFT']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trends_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['forecasting',</span> <span class="pre">'cycling',</span> <span class="pre">'microsoft']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trends_geo</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_data_types</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['AWND',</span> <span class="pre">'WSF2',</span> <span class="pre">'TAVG']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_stations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['USW00094846',</span> <span class="pre">'USW00014925']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_years</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_stations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['CT3',</span> <span class="pre">'SK8']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_species</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PM25'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_days</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">earthquake_days</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">earthquake_min_magnitude</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gsa_key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gov_domain_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['nasa.gov']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gov_domain_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">600</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wikipedia_pages</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Microsoft_Office',</span> <span class="pre">'List_of_highest-grossing_films']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wiki_language</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'en'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_event_types</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['%28Z%29+Winter+Weather',</span> <span class="pre">'%28Z%29+Winter+Storm']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">caiso_query</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ENE_SLRS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">timeout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">300.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sleep_seconds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_live_daily" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_live_daily</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_start</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_end</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fred_key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fred_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['DGS10',</span> <span class="pre">'T5YIE',</span> <span class="pre">'SP500',</span> <span class="pre">'DCOILWTICO',</span> <span class="pre">'DEXUSEU',</span> <span class="pre">'WPU0911']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tickers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['MSFT']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trends_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['forecasting',</span> <span class="pre">'cycling',</span> <span class="pre">'microsoft']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trends_geo</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_data_types</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['AWND',</span> <span class="pre">'WSF2',</span> <span class="pre">'TAVG']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_stations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['USW00094846',</span> <span class="pre">'USW00014925']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_years</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_stations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['CT3',</span> <span class="pre">'SK8']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_species</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PM25'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_days</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">earthquake_days</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">earthquake_min_magnitude</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gsa_key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gov_domain_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['nasa.gov']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gov_domain_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">600</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wikipedia_pages</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Microsoft_Office',</span> <span class="pre">'List_of_highest-grossing_films']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wiki_language</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'en'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_event_types</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['%28Z%29+Winter+Weather',</span> <span class="pre">'%28Z%29+Winter+Storm']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">caiso_query</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ENE_SLRS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">timeout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">300.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sleep_seconds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_live_daily" title="Link to this definition">¶</a></dt>
 <dd><p>Generates a dataframe of data up to the present day. Requires active internet connection.
 Try to be respectful of these free data sources by not calling too much too heavily.
 Pass None instead of specification lists to exclude a data source.</p>
@@ -167,19 +175,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_monthly">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_monthly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_monthly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_monthly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_monthly" title="Link to this definition">¶</a></dt>
 <dd><p>Federal Reserve of St. Louis monthly economic indicators.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_sine">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_sine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_random</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_sine" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_sine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_random</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_sine" title="Link to this definition">¶</a></dt>
 <dd><p>Create a dataset of just zeroes for testing edge case.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_weekdays">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_weekdays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_weekdays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_weekdays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_weekdays" title="Link to this definition">¶</a></dt>
 <dd><p>Test edge cases by creating a Series with values as day of week.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -195,19 +203,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_weekly">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_weekly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_weekly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_weekly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_weekly" title="Link to this definition">¶</a></dt>
 <dd><p>Weekly petroleum industry data from the EIA.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_yearly">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_yearly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_yearly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_yearly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_yearly" title="Link to this definition">¶</a></dt>
 <dd><p>Federal Reserve of St. Louis annual economic indicators.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.datasets.load_zeroes">
-<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_zeroes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_zeroes" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.datasets.</span></span><span class="sig-name descname"><span class="pre">load_zeroes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.datasets.load_zeroes" title="Link to this definition">¶</a></dt>
 <dd><p>Create a dataset of just zeroes for testing edge case.</p>
 </dd></dl>
 
@@ -304,21 +312,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/source/autots.evaluator.html b/docs/build/html/source/autots.evaluator.html
index 4ff67144..9a19062a 100644
--- a/docs/build/html/source/autots.evaluator.html
+++ b/docs/build/html/source/autots.evaluator.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="../">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>autots.evaluator package &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
-    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/doctools.js"></script>
-    <script src="../_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css?v=a4fa0645" />
+    <script src="../_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="../_static/doctools.js?v=888ff710"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
     <link rel="next" title="autots.models package" href="autots.models.html" />
@@ -33,22 +41,22 @@
           <div class="body" role="main">
             
   <section id="autots-evaluator-package">
-<h1>autots.evaluator package<a class="headerlink" href="#autots-evaluator-package" title="Permalink to this heading">¶</a></h1>
+<h1>autots.evaluator package<a class="headerlink" href="#autots-evaluator-package" title="Link to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading">¶</a></h2>
 </section>
 <section id="module-autots.evaluator.anomaly_detector">
-<span id="autots-evaluator-anomaly-detector-module"></span><h2>autots.evaluator.anomaly_detector module<a class="headerlink" href="#module-autots.evaluator.anomaly_detector" title="Permalink to this heading">¶</a></h2>
+<span id="autots-evaluator-anomaly-detector-module"></span><h2>autots.evaluator.anomaly_detector module<a class="headerlink" href="#module-autots.evaluator.anomaly_detector" title="Link to this heading">¶</a></h2>
 <p>Anomaly Detector
 Created on Mon Jul 18 14:19:55 2022</p>
 <p>&#64;author: Colin</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.AnomalyDetector">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">AnomalyDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zscore'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'transformation_params':</span> <span class="pre">{0:</span> <span class="pre">{'datepart_method':</span> <span class="pre">'simple_3',</span> <span class="pre">'regression_model':</span> <span class="pre">{'model':</span> <span class="pre">'ElasticNet',</span> <span class="pre">'model_params':</span> <span class="pre">{}}}},</span> <span class="pre">'transformations':</span> <span class="pre">{0:</span> <span class="pre">'DatepartRegression'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">isolated_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">AnomalyDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zscore'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'transformation_params':</span> <span class="pre">{0:</span> <span class="pre">{'datepart_method':</span> <span class="pre">'simple_3',</span> <span class="pre">'regression_model':</span> <span class="pre">{'model':</span> <span class="pre">'ElasticNet',</span> <span class="pre">'model_params':</span> <span class="pre">{}}}},</span> <span class="pre">'transformations':</span> <span class="pre">{0:</span> <span class="pre">'DatepartRegression'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">isolated_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.AnomalyDetector.detect">
-<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.detect" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.detect" title="Link to this definition">¶</a></dt>
 <dd><p>All will return -1 for anomalies.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -62,18 +70,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.AnomalyDetector.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.AnomalyDetector.fit_anomaly_classifier">
-<span class="sig-name descname"><span class="pre">fit_anomaly_classifier</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.fit_anomaly_classifier" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_anomaly_classifier</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.fit_anomaly_classifier" title="Link to this definition">¶</a></dt>
 <dd><p>Fit a model to predict if a score is an anomaly.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.AnomalyDetector.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate random new parameter combinations.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -84,12 +92,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.AnomalyDetector.plot">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.plot" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.plot" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.AnomalyDetector.score_to_anomaly">
-<span class="sig-name descname"><span class="pre">score_to_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scores</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.score_to_anomaly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">score_to_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scores</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.AnomalyDetector.score_to_anomaly" title="Link to this definition">¶</a></dt>
 <dd><p>A DecisionTree model, used as models are nonstandard (and nonparametric).</p>
 </dd></dl>
 
@@ -97,11 +105,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.HolidayDetector">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">HolidayDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_occurrences</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">splash_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.65</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dayofmonth_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">HolidayDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_occurrences</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">splash_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.65</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dayofmonth_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.HolidayDetector.dates_to_holidays">
-<span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">style</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.dates_to_holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">style</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.dates_to_holidays" title="Link to this definition">¶</a></dt>
 <dd><p>Populate date information for a given pd.DatetimeIndex.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -122,39 +130,39 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.HolidayDetector.detect">
-<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.detect" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.detect" title="Link to this definition">¶</a></dt>
 <dd><p>Run holiday detection. Input wide-style pandas time series.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.HolidayDetector.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.HolidayDetector.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.get_new_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.HolidayDetector.plot">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_anomalies</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.plot" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_anomalies</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.plot" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.anomaly_detector.HolidayDetector.plot_anomaly">
-<span class="sig-name descname"><span class="pre">plot_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.plot_anomaly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.anomaly_detector.HolidayDetector.plot_anomaly" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 </section>
 <section id="module-autots.evaluator.auto_model">
-<span id="autots-evaluator-auto-model-module"></span><h2>autots.evaluator.auto_model module<a class="headerlink" href="#module-autots.evaluator.auto_model" title="Permalink to this heading">¶</a></h2>
+<span id="autots-evaluator-auto-model-module"></span><h2>autots.evaluator.auto_model module<a class="headerlink" href="#module-autots.evaluator.auto_model" title="Link to this heading">¶</a></h2>
 <p>Mid-level helper functions for AutoTS.</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.ModelMonster">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">ModelMonster</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parameters</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelMonster" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">ModelMonster</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parameters</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelMonster" title="Link to this definition">¶</a></dt>
 <dd><p>Directs strings and parameters to appropriate model objects.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -168,7 +176,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.ModelPrediction">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">ModelPrediction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_str</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parameter_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelPrediction" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">ModelPrediction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_str</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parameter_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelPrediction" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="autots.models.html#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Feed parameters into modeling pipeline. A class object, does NOT work with ensembles.</p>
 <dl class="field-list simple">
@@ -201,24 +209,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.ModelPrediction.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelPrediction.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelPrediction.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.ModelPrediction.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelPrediction.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelPrediction.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.ModelPrediction.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelPrediction.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.ModelPrediction.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.NewGeneticTemplate">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">NewGeneticTemplate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">submitted_parameters</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sort_column</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Score'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sort_ascending</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_results</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">top_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">score_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">recursive_count</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.NewGeneticTemplate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">NewGeneticTemplate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">submitted_parameters</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sort_column</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Score'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sort_ascending</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_results</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">top_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">score_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">recursive_count</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.NewGeneticTemplate" title="Link to this definition">¶</a></dt>
 <dd><p>Return new template given old template with model accuracies.</p>
 <p>“No mating!” - Pattern, Sanderson</p>
 <dl class="field-list simple">
@@ -233,7 +241,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.RandomTemplate">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">RandomTemplate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['ZeroesNaive',</span> <span class="pre">'LastValueNaive',</span> <span class="pre">'AverageValueNaive',</span> <span class="pre">'GLS',</span> <span class="pre">'GLM',</span> <span class="pre">'ETS']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'fast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.RandomTemplate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">RandomTemplate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['ZeroesNaive',</span> <span class="pre">'LastValueNaive',</span> <span class="pre">'AverageValueNaive',</span> <span class="pre">'GLS',</span> <span class="pre">'GLM',</span> <span class="pre">'ETS']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'fast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.RandomTemplate" title="Link to this definition">¶</a></dt>
 <dd><p>Returns a template dataframe of randomly generated transformations, models, and hyperparameters.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -244,12 +252,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.TemplateEvalObject">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">TemplateEvalObject</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_results=Empty</span> <span class="pre">DataFrame</span> <span class="pre">Columns:</span> <span class="pre">[]</span> <span class="pre">Index:</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_timestamp_smape=Empty</span> <span class="pre">DataFrame</span> <span class="pre">Columns:</span> <span class="pre">[]</span> <span class="pre">Index:</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_metrics=Empty</span> <span class="pre">DataFrame</span> <span class="pre">Columns:</span> <span class="pre">[]</span> <span class="pre">Index:</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_mae=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_rmse=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_made=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_contour=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_spl=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_mle=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_imle=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_maxe=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_oda=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_mqae=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_dwae=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_ewmae=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_uwmse=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_smoothness=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_mate=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_matse=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_wasserstein=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_dwd=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">TemplateEvalObject</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_results=Empty</span> <span class="pre">DataFrame</span> <span class="pre">Columns:</span> <span class="pre">[]</span> <span class="pre">Index:</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_timestamp_smape=Empty</span> <span class="pre">DataFrame</span> <span class="pre">Columns:</span> <span class="pre">[]</span> <span class="pre">Index:</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_metrics=Empty</span> <span class="pre">DataFrame</span> <span class="pre">Columns:</span> <span class="pre">[]</span> <span class="pre">Index:</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_mae=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_rmse=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_made=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_contour=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_spl=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_mle=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_imle=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_maxe=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_oda=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_mqae=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_dwae=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_ewmae=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_uwmse=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_smoothness=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_mate=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_matse=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_wasserstein=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_dwd=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Object to contain all the failures!.</p>
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.TemplateEvalObject.full_mae_ids">
-<span class="sig-name descname"><span class="pre">full_mae_ids</span></span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.full_mae_ids" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">full_mae_ids</span></span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.full_mae_ids" title="Link to this definition">¶</a></dt>
 <dd><p>list of model_ids corresponding to full_mae_errors</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -260,7 +268,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.TemplateEvalObject.full_mae_errors">
-<span class="sig-name descname"><span class="pre">full_mae_errors</span></span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.full_mae_errors" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">full_mae_errors</span></span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.full_mae_errors" title="Link to this definition">¶</a></dt>
 <dd><p>list of numpy arrays of shape (rows, columns) appended in order of validation
 only provided for ‘mosaic’ ensembling</p>
 <dl class="field-list simple">
@@ -272,18 +280,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.TemplateEvalObject.concat">
-<span class="sig-name descname"><span class="pre">concat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">another_eval</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.concat" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">concat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">another_eval</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.concat" title="Link to this definition">¶</a></dt>
 <dd><p>Merge another TemplateEvalObject onto this one.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.TemplateEvalObject.load">
-<span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.load" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.load" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.TemplateEvalObject.save">
-<span class="sig-name descname"><span class="pre">save</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'initial_results.pickle'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.save" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">save</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'initial_results.pickle'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateEvalObject.save" title="Link to this definition">¶</a></dt>
 <dd><p>Save results to a file.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -296,7 +304,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.TemplateWizard">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">TemplateWizard</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">template</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['mosaic',</span> <span class="pre">'distance']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_round</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_generation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_generations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'0'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_interrupt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">traceback</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mosaic_used</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_msg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateWizard" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">TemplateWizard</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">template</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['mosaic',</span> <span class="pre">'distance']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_round</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_generation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_generations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'0'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_interrupt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">traceback</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mosaic_used</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_msg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.TemplateWizard" title="Link to this definition">¶</a></dt>
 <dd><p>Take Template, returns Results.</p>
 <p>There are some who call me… Tim. - Python</p>
 <dl class="field-list simple">
@@ -336,7 +344,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.UniqueTemplates">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">UniqueTemplates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">existing_templates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new_possibilities</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">selection_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.UniqueTemplates" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">UniqueTemplates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">existing_templates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new_possibilities</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">selection_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.UniqueTemplates" title="Link to this definition">¶</a></dt>
 <dd><p>Returns unique dataframe rows from new_possiblities not in existing_templates.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -347,7 +355,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.back_forecast">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">123</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.back_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">123</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.back_forecast" title="Link to this definition">¶</a></dt>
 <dd><p>Create forecasts for the historical training data, ie. backcast or back forecast.</p>
 <p>This actually forecasts on historical data, these are not fit model values as are often returned by other packages.
 As such, this will be slower, but more representative of real world model performance.
@@ -364,19 +372,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.create_model_id">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">create_model_id</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_str</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parameter_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.create_model_id" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">create_model_id</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_str</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parameter_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.create_model_id" title="Link to this definition">¶</a></dt>
 <dd><p>Create a hash ID which should be unique to the model parameters.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.dict_recombination">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">dict_recombination</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">b</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.dict_recombination" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">dict_recombination</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">b</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.dict_recombination" title="Link to this definition">¶</a></dt>
 <dd><p>Recombine two dictionaries with identical keys. Return new dict.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.generate_score">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">generate_score</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_weighting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.generate_score" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">generate_score</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_weighting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.generate_score" title="Link to this definition">¶</a></dt>
 <dd><p>Generate score based on relative accuracies.</p>
 <p>SMAPE - smaller is better
 MAE - smaller is better
@@ -394,19 +402,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.generate_score_per_series">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">generate_score_per_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">results_object</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_weighting</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">total_validations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_use</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.generate_score_per_series" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">generate_score_per_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">results_object</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_weighting</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">total_validations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_use</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.generate_score_per_series" title="Link to this definition">¶</a></dt>
 <dd><p>Score generation on per_series_metrics for ensembles.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.horizontal_template_to_model_list">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">horizontal_template_to_model_list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">template</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.horizontal_template_to_model_list" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">horizontal_template_to_model_list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">template</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.horizontal_template_to_model_list" title="Link to this definition">¶</a></dt>
 <dd><p>helper function to take template dataframe of ensembles to a single list of models.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.model_forecast">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">model_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">horizontal_subset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.model_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">model_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">horizontal_subset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.model_forecast" title="Link to this definition">¶</a></dt>
 <dd><p>Takes numeric data, returns numeric forecasts.</p>
 <p>Only one model (albeit potentially an ensemble)!
 Horizontal ensembles can not be nested, other ensemble types can be.</p>
@@ -449,25 +457,25 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.random_model">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">random_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_prob</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">counter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">15</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keyword_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.random_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">random_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_prob</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">counter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">15</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keyword_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.random_model" title="Link to this definition">¶</a></dt>
 <dd><p>Generate a random model from a given list of models and probabilities.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.remove_leading_zeros">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">remove_leading_zeros</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.remove_leading_zeros" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">remove_leading_zeros</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.remove_leading_zeros" title="Link to this definition">¶</a></dt>
 <dd><p>Accepts wide dataframe, returns dataframe with zeroes preceeding any non-zero value as NaN.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.trans_dict_recomb">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">trans_dict_recomb</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dict_array</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.trans_dict_recomb" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">trans_dict_recomb</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dict_array</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.trans_dict_recomb" title="Link to this definition">¶</a></dt>
 <dd><p>Recombine two transformation param dictionaries from array of dicts.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.unpack_ensemble_models">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">unpack_ensemble_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">template</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keep_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">recursive</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.unpack_ensemble_models" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">unpack_ensemble_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">template</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keep_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">recursive</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.unpack_ensemble_models" title="Link to this definition">¶</a></dt>
 <dd><p>Take ensemble models from template and add as new rows.
 Some confusion may exist as Ensembles require both ‘Ensemble’ column &gt; 0 and model name ‘Ensemble’</p>
 <dl class="field-list simple">
@@ -483,17 +491,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_model.validation_aggregation">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">validation_aggregation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">validation_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">groupby_cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['ID',</span> <span class="pre">'Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.validation_aggregation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_model.</span></span><span class="sig-name descname"><span class="pre">validation_aggregation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">validation_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">groupby_cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['ID',</span> <span class="pre">'Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_model.validation_aggregation" title="Link to this definition">¶</a></dt>
 <dd><p>Aggregate a TemplateEvalObject.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.evaluator.auto_ts">
-<span id="autots-evaluator-auto-ts-module"></span><h2>autots.evaluator.auto_ts module<a class="headerlink" href="#module-autots.evaluator.auto_ts" title="Permalink to this heading">¶</a></h2>
+<span id="autots-evaluator-auto-ts-module"></span><h2>autots.evaluator.auto_ts module<a class="headerlink" href="#module-autots.evaluator.auto_ts" title="Link to this heading">¶</a></h2>
 <p>Higher-level functions of automated time series modeling.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_ts.</span></span><span class="sig-name descname"><span class="pre">AutoTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_generations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_template</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'General+Random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_weighting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'containment_weighting':</span> <span class="pre">0,</span> <span class="pre">'contour_weighting':</span> <span class="pre">0.01,</span> <span class="pre">'imle_weighting':</span> <span class="pre">0,</span> <span class="pre">'made_weighting':</span> <span class="pre">0.05,</span> <span class="pre">'mae_weighting':</span> <span class="pre">2,</span> <span class="pre">'mage_weighting':</span> <span class="pre">0,</span> <span class="pre">'mle_weighting':</span> <span class="pre">0,</span> <span class="pre">'oda_weighting':</span> <span class="pre">0.001,</span> <span class="pre">'rmse_weighting':</span> <span class="pre">2,</span> <span class="pre">'runtime_weighting':</span> <span class="pre">0.01,</span> <span class="pre">'smape_weighting':</span> <span class="pre">5,</span> <span class="pre">'spl_weighting':</span> <span class="pre">3,</span> <span class="pre">'wasserstein_weighting':</span> <span class="pre">0.01}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_data_older_than_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_validate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.15</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'backwards'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_leading_zeroes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preclean</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_interrupt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">generation_timeout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_ts.</span></span><span class="sig-name descname"><span class="pre">AutoTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_generations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_template</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'General+Random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_weighting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'containment_weighting':</span> <span class="pre">0,</span> <span class="pre">'contour_weighting':</span> <span class="pre">0.01,</span> <span class="pre">'imle_weighting':</span> <span class="pre">0,</span> <span class="pre">'made_weighting':</span> <span class="pre">0.05,</span> <span class="pre">'mae_weighting':</span> <span class="pre">2,</span> <span class="pre">'mage_weighting':</span> <span class="pre">0,</span> <span class="pre">'mle_weighting':</span> <span class="pre">0,</span> <span class="pre">'oda_weighting':</span> <span class="pre">0.001,</span> <span class="pre">'rmse_weighting':</span> <span class="pre">2,</span> <span class="pre">'runtime_weighting':</span> <span class="pre">0.01,</span> <span class="pre">'smape_weighting':</span> <span class="pre">5,</span> <span class="pre">'spl_weighting':</span> <span class="pre">3,</span> <span class="pre">'wasserstein_weighting':</span> <span class="pre">0.01}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_data_older_than_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_validate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.15</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'backwards'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_leading_zeroes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preclean</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_interrupt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">generation_timeout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Automate time series modeling using a genetic algorithm.</p>
 <dl class="field-list simple">
@@ -588,7 +596,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.best_model">
-<span class="sig-name descname"><span class="pre">best_model</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model" title="Link to this definition">¶</a></dt>
 <dd><p>DataFrame containing template for the best ranked model</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -599,7 +607,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.best_model_name">
-<span class="sig-name descname"><span class="pre">best_model_name</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_name" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_name</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_name" title="Link to this definition">¶</a></dt>
 <dd><p>model name</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -610,7 +618,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.best_model_params">
-<span class="sig-name descname"><span class="pre">best_model_params</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_params</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_params" title="Link to this definition">¶</a></dt>
 <dd><p>model params</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -621,7 +629,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.best_model_transformation_params">
-<span class="sig-name descname"><span class="pre">best_model_transformation_params</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_transformation_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_transformation_params</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_transformation_params" title="Link to this definition">¶</a></dt>
 <dd><p>transformation parameters</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -632,7 +640,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.best_model_ensemble">
-<span class="sig-name descname"><span class="pre">best_model_ensemble</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_ensemble" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_ensemble</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_ensemble" title="Link to this definition">¶</a></dt>
 <dd><p>Ensemble type int id</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -643,7 +651,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.regression_check">
-<span class="sig-name descname"><span class="pre">regression_check</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.regression_check" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">regression_check</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.regression_check" title="Link to this definition">¶</a></dt>
 <dd><p>If True, the best_model uses an input ‘User’ future_regressor</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -654,7 +662,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.df_wide_numeric">
-<span class="sig-name descname"><span class="pre">df_wide_numeric</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.df_wide_numeric" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">df_wide_numeric</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.df_wide_numeric" title="Link to this definition">¶</a></dt>
 <dd><p>dataframe containing shaped final data, will include preclean</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -665,7 +673,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.initial_results.model_results">
-<span class="sig-prename descclassname"><span class="pre">initial_results.</span></span><span class="sig-name descname"><span class="pre">model_results</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.initial_results.model_results" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">initial_results.</span></span><span class="sig-name descname"><span class="pre">model_results</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.initial_results.model_results" title="Link to this definition">¶</a></dt>
 <dd><p>contains a collection of result metrics</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -676,7 +684,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.score_per_series">
-<span class="sig-name descname"><span class="pre">score_per_series</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.score_per_series" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">score_per_series</span></span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.score_per_series" title="Link to this definition">¶</a></dt>
 <dd><p>generated score of metrics given per input series, if horizontal ensembles</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -712,7 +720,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.back_forecast">
-<span class="sig-name descname"><span class="pre">back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tail</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.back_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tail</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.back_forecast" title="Link to this definition">¶</a></dt>
 <dd><p>Create forecasts for the historical training data, ie. backcast or back forecast. OUT OF SAMPLE</p>
 <p>This actually forecasts on historical data, these are not fit model values as are often returned by other packages.
 As such, this will be slower, but more representative of real world model performance.
@@ -729,18 +737,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.best_model_per_series_mape">
-<span class="sig-name descname"><span class="pre">best_model_per_series_mape</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_per_series_mape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_per_series_mape</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_per_series_mape" title="Link to this definition">¶</a></dt>
 <dd><p>This isn’t quite classic mape but is a percentage mean error intended for quick visuals not final statistics (see model.results()).</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.best_model_per_series_score">
-<span class="sig-name descname"><span class="pre">best_model_per_series_score</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_per_series_score" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_per_series_score</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.best_model_per_series_score" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.diagnose_params">
-<span class="sig-name descname"><span class="pre">diagnose_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'runtime'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">waterfall_plots</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.diagnose_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">diagnose_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'runtime'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">waterfall_plots</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.diagnose_params" title="Link to this definition">¶</a></dt>
 <dd><p>Attempt to explain params causing measured outcomes using shap and linear regression coefficients.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -754,20 +762,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.expand_horizontal">
-<span class="sig-name descname"><span class="pre">expand_horizontal</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.expand_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">expand_horizontal</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.expand_horizontal" title="Link to this definition">¶</a></dt>
 <dd><p>Enables expanding horizontal models trained on a subset to full data.
 Reruns template models and generates new template.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.export_best_model">
-<span class="sig-name descname"><span class="pre">export_best_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.export_best_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">export_best_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.export_best_model" title="Link to this definition">¶</a></dt>
 <dd><p>Basically the same as export_template but only ever the one best model.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.export_template">
-<span class="sig-name descname"><span class="pre">export_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'best'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">40</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_results</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unpack_ensembles</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_metrics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['smape',</span> <span class="pre">'spl']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_metrics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.export_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">export_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'best'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">40</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_results</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unpack_ensembles</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_metrics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['smape',</span> <span class="pre">'spl']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_metrics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.export_template" title="Link to this definition">¶</a></dt>
 <dd><p>Export top results as a reusable template.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -789,7 +797,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.failure_rate">
-<span class="sig-name descname"><span class="pre">failure_rate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'initial'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.failure_rate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">failure_rate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'initial'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.failure_rate" title="Link to this definition">¶</a></dt>
 <dd><p>Return fraction of models passing with exceptions.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -803,7 +811,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_indexes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_indexes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -828,13 +836,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.fit_data" title="Link to this definition">¶</a></dt>
 <dd><p>Part of the setup that involves fitting the initial data but not running any models.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.get_metric_corr">
-<span class="sig-name descname"><span class="pre">get_metric_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">percent_best</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.get_metric_corr" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_metric_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">percent_best</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.get_metric_corr" title="Link to this definition">¶</a></dt>
 <dd><p>Returns a dataframe of correlation among evaluation metrics across evaluations.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -845,24 +853,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Randomly generate new parameters for the class.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.horizontal_per_generation">
-<span class="sig-name descname"><span class="pre">horizontal_per_generation</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.horizontal_per_generation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">horizontal_per_generation</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.horizontal_per_generation" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.horizontal_to_df">
-<span class="sig-name descname"><span class="pre">horizontal_to_df</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.horizontal_to_df" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">horizontal_to_df</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.horizontal_to_df" title="Link to this definition">¶</a></dt>
 <dd><p>helper function for plotting.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.import_best_model">
-<span class="sig-name descname"><span class="pre">import_best_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">import_target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enforce_model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.import_best_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">import_best_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">import_target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enforce_model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.import_best_model" title="Link to this definition">¶</a></dt>
 <dd><p>Load a best model, overriding any existing setting.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -873,7 +881,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.import_results">
-<span class="sig-name descname"><span class="pre">import_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.import_results" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">import_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.import_results" title="Link to this definition">¶</a></dt>
 <dd><p>Add results from another run on the same data.</p>
 <p>Input can be filename with .csv or .pickle.
 or can be a DataFrame of model results or a full TemplateEvalObject</p>
@@ -881,7 +889,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.import_template">
-<span class="sig-name descname"><span class="pre">import_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'add_on'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enforce_model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_horizontal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_validation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.import_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">import_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'add_on'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enforce_model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_horizontal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_validation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.import_template" title="Link to this definition">¶</a></dt>
 <dd><p>Import a previously exported template of model parameters.
 Must be done before the AutoTS object is .fit().</p>
 <dl class="field-list simple">
@@ -901,36 +909,36 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.list_failed_model_types">
-<span class="sig-name descname"><span class="pre">list_failed_model_types</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.list_failed_model_types" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">list_failed_model_types</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.list_failed_model_types" title="Link to this definition">¶</a></dt>
 <dd><p>Return a list of model types (ie ETS, LastValueNaive) that failed.
 If all had at least one success, then return an empty list.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.load_template">
-<span class="sig-name descname"><span class="pre">load_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.load_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">load_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.load_template" title="Link to this definition">¶</a></dt>
 <dd><p>Helper funciton for just loading the file part of import_template.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.mosaic_to_df">
-<span class="sig-name descname"><span class="pre">mosaic_to_df</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.mosaic_to_df" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">mosaic_to_df</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.mosaic_to_df" title="Link to this definition">¶</a></dt>
 <dd><p>Helper function to create a readable df of models in mosaic.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.parse_best_model">
-<span class="sig-name descname"><span class="pre">parse_best_model</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.parse_best_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">parse_best_model</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.parse_best_model" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_back_forecast">
-<span class="sig-name descname"><span class="pre">plot_back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_back_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_back_forecast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_backforecast">
-<span class="sig-name descname"><span class="pre">plot_backforecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">facecolor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'black'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper</span> <span class="pre">left'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_backforecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_backforecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">facecolor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'black'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper</span> <span class="pre">left'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_backforecast" title="Link to this definition">¶</a></dt>
 <dd><p>Plot the historical data and fit forecast on historic. Out of sample in chunks = forecast_length by default.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -947,7 +955,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_generation_loss">
-<span class="sig-name descname"><span class="pre">plot_generation_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Single</span> <span class="pre">Model</span> <span class="pre">Accuracy</span> <span class="pre">Gain</span> <span class="pre">Over</span> <span class="pre">Generations'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_generation_loss" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_generation_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Single</span> <span class="pre">Model</span> <span class="pre">Accuracy</span> <span class="pre">Gain</span> <span class="pre">Over</span> <span class="pre">Generations'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_generation_loss" title="Link to this definition">¶</a></dt>
 <dd><p>Plot improvement in accuracy over generations.
 Note: this is only “one size fits all” accuracy and
 doesn’t account for the benefits seen for ensembling.</p>
@@ -960,7 +968,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_horizontal">
-<span class="sig-name descname"><span class="pre">plot_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Model</span> <span class="pre">Types</span> <span class="pre">Chosen</span> <span class="pre">by</span> <span class="pre">Series'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Model</span> <span class="pre">Types</span> <span class="pre">Chosen</span> <span class="pre">by</span> <span class="pre">Series'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_horizontal" title="Link to this definition">¶</a></dt>
 <dd><p>Simple plot to visualize assigned series: models.</p>
 <p>Note that for ‘mosaic’ ensembles, it only plots the type of the most common model_id for that series, or the first if all are mode.</p>
 <dl class="field-list simple">
@@ -975,19 +983,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_horizontal_model_count">
-<span class="sig-name descname"><span class="pre">plot_horizontal_model_count</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">color_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">top_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Most</span> <span class="pre">Frequently</span> <span class="pre">Chosen</span> <span class="pre">Models'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_horizontal_model_count" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_horizontal_model_count</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">color_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">top_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Most</span> <span class="pre">Frequently</span> <span class="pre">Chosen</span> <span class="pre">Models'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_horizontal_model_count" title="Link to this definition">¶</a></dt>
 <dd><p>Plots most common models. Does not factor in nested in non-horizontal Ensembles.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_horizontal_per_generation">
-<span class="sig-name descname"><span class="pre">plot_horizontal_per_generation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Horizontal</span> <span class="pre">Ensemble</span> <span class="pre">Accuracy</span> <span class="pre">Gain</span> <span class="pre">(first</span> <span class="pre">eval</span> <span class="pre">sample</span> <span class="pre">only)'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_horizontal_per_generation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_horizontal_per_generation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Horizontal</span> <span class="pre">Ensemble</span> <span class="pre">Accuracy</span> <span class="pre">Gain</span> <span class="pre">(first</span> <span class="pre">eval</span> <span class="pre">sample</span> <span class="pre">only)'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_horizontal_per_generation" title="Link to this definition">¶</a></dt>
 <dd><p>Plot how well the horizontal ensembles would do after each new generation. Slow.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_horizontal_transformers">
-<span class="sig-name descname"><span class="pre">plot_horizontal_transformers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'transformers'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_horizontal_transformers" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_horizontal_transformers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'transformers'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_horizontal_transformers" title="Link to this definition">¶</a></dt>
 <dd><p>Simple plot to visualize transformers used.
 Note this doesn’t capture transformers nested in simple ensembles.</p>
 <dl class="field-list simple">
@@ -1003,7 +1011,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_metric_corr">
-<span class="sig-name descname"><span class="pre">plot_metric_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percent_best</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_metric_corr" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_metric_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percent_best</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_metric_corr" title="Link to this definition">¶</a></dt>
 <dd><p>Plot correlation in results among metrics.
 The metrics that are highly correlated are those that mostly the unscaled ones</p>
 <dl class="field-list simple">
@@ -1018,7 +1026,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_per_series_error">
-<span class="sig-name descname"><span class="pre">plot_per_series_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Top</span> <span class="pre">Series</span> <span class="pre">Contributing</span> <span class="pre">Score</span> <span class="pre">Error'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_clip</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_per_series_error" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_per_series_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Top</span> <span class="pre">Series</span> <span class="pre">Contributing</span> <span class="pre">Score</span> <span class="pre">Error'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_clip</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_per_series_error" title="Link to this definition">¶</a></dt>
 <dd><p>Plot which series are contributing most to error (Score) of final model. Avg of validations for best_model</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1038,7 +1046,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_per_series_mape">
-<span class="sig-name descname"><span class="pre">plot_per_series_mape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_per_series_mape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_per_series_mape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_per_series_mape" title="Link to this definition">¶</a></dt>
 <dd><p>Plot which series are contributing most to SMAPE of final model. Avg of validations for best_model</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1057,19 +1065,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_per_series_smape">
-<span class="sig-name descname"><span class="pre">plot_per_series_smape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_per_series_smape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_per_series_smape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_per_series_smape" title="Link to this definition">¶</a></dt>
 <dd><p>To be backwards compatible, not necessarily maintained, plot_per_series_mape is to be preferred.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_transformer_failure_rate">
-<span class="sig-name descname"><span class="pre">plot_transformer_failure_rate</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_transformer_failure_rate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_transformer_failure_rate</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_transformer_failure_rate" title="Link to this definition">¶</a></dt>
 <dd><p>Failure Rate per Transformer type (ignoring ensembles), failure may be due to other model or transformer.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.plot_validations">
-<span class="sig-name descname"><span class="pre">plot_validations</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">end_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compare_horizontal</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.35</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkred'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">end_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#A2AD9C'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_validations" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_validations</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">end_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compare_horizontal</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.35</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkred'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">end_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#A2AD9C'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.plot_validations" title="Link to this definition">¶</a></dt>
 <dd><p>Similar to plot_backforecast but using the model’s validation segments specifically. Must reforecast.
 Saves results to self.validation_forecasts and caches. Set that to None to force rerun otherwise it uses stored (when models is the same).
 ‘chosen’ refers to best_model_id, the model chosen to run for predict
@@ -1094,7 +1102,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hierarchy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hierarchy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <p>If using a model from update_fit list, with no ensembling, underlying model will not be retrained when used as below, with a single prediction interval:
 This designed for high speed forecasting. Full retraining is best when there is sufficient time.
@@ -1137,7 +1145,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.results">
-<span class="sig-name descname"><span class="pre">results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'initial'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.results" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'initial'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.results" title="Link to this definition">¶</a></dt>
 <dd><p>Convenience function to return tested models table.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1148,25 +1156,25 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.retrieve_validation_forecasts">
-<span class="sig-name descname"><span class="pre">retrieve_validation_forecasts</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compare_horizontal</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeriesID'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interval_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'PredictionInterval'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.retrieve_validation_forecasts" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">retrieve_validation_forecasts</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compare_horizontal</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeriesID'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interval_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'PredictionInterval'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.retrieve_validation_forecasts" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.save_template">
-<span class="sig-name descname"><span class="pre">save_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">export_template</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.save_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">save_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">export_template</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.save_template" title="Link to this definition">¶</a></dt>
 <dd><p>Helper function for the save part of export_template.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.AutoTS.validation_agg">
-<span class="sig-name descname"><span class="pre">validation_agg</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.validation_agg" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">validation_agg</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.AutoTS.validation_agg" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.error_correlations">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_ts.</span></span><span class="sig-name descname"><span class="pre">error_correlations</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">all_result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'corr'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.error_correlations" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_ts.</span></span><span class="sig-name descname"><span class="pre">error_correlations</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">all_result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'corr'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.error_correlations" title="Link to this definition">¶</a></dt>
 <dd><p>Onehot encode AutoTS result df and return df or correlation with errors.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1180,22 +1188,22 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.auto_ts.fake_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_ts.</span></span><span class="sig-name descname"><span class="pre">fake_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.95</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_data_older_than_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dimensions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.fake_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.auto_ts.</span></span><span class="sig-name descname"><span class="pre">fake_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.95</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_data_older_than_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dimensions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.auto_ts.fake_regressor" title="Link to this definition">¶</a></dt>
 <dd><p>Create a fake regressor of random numbers for testing purposes.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.evaluator.benchmark">
-<span id="autots-evaluator-benchmark-module"></span><h2>autots.evaluator.benchmark module<a class="headerlink" href="#module-autots.evaluator.benchmark" title="Permalink to this heading">¶</a></h2>
+<span id="autots-evaluator-benchmark-module"></span><h2>autots.evaluator.benchmark module<a class="headerlink" href="#module-autots.evaluator.benchmark" title="Link to this heading">¶</a></h2>
 <p>Created on Fri Nov  5 13:45:01 2021</p>
 <p>&#64;author: Colin</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.evaluator.benchmark.Benchmark">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.benchmark.</span></span><span class="sig-name descname"><span class="pre">Benchmark</span></span><a class="headerlink" href="#autots.evaluator.benchmark.Benchmark" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.benchmark.</span></span><span class="sig-name descname"><span class="pre">Benchmark</span></span><a class="headerlink" href="#autots.evaluator.benchmark.Benchmark" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.benchmark.Benchmark.run">
-<span class="sig-name descname"><span class="pre">run</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">times</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">base_models_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.benchmark.Benchmark.run" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">run</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">times</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">base_models_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.benchmark.Benchmark.run" title="Link to this definition">¶</a></dt>
 <dd><p>Run benchmark.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1213,12 +1221,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.evaluator.event_forecasting">
-<span id="autots-evaluator-event-forecasting-module"></span><h2>autots.evaluator.event_forecasting module<a class="headerlink" href="#module-autots.evaluator.event_forecasting" title="Permalink to this heading">¶</a></h2>
+<span id="autots-evaluator-event-forecasting-module"></span><h2>autots.evaluator.event_forecasting module<a class="headerlink" href="#module-autots.evaluator.event_forecasting" title="Link to this heading">¶</a></h2>
 <p>Generate probabilities of forecastings crossing limit thresholds.
 Created on Thu Jan 27 13:36:18 2022</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">EventRiskForecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.95</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'UnivariateMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'distance_metric':</span> <span class="pre">'euclidean',</span> <span class="pre">'k':</span> <span class="pre">10,</span> <span class="pre">'pointed_method':</span> <span class="pre">'median',</span> <span class="pre">'return_result_windows':</span> <span class="pre">True,</span> <span class="pre">'window':</span> <span class="pre">14}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'fillna':</span> <span class="pre">'pchip',</span> <span class="pre">'transformation_params':</span> <span class="pre">{'0':</span> <span class="pre">{'method':</span> <span class="pre">0.5},</span> <span class="pre">'1':</span> <span class="pre">{},</span> <span class="pre">'2':</span> <span class="pre">{'fixed':</span> <span class="pre">False,</span> <span class="pre">'window':</span> <span class="pre">7},</span> <span class="pre">'3':</span> <span class="pre">{}},</span> <span class="pre">'transformations':</span> <span class="pre">{'0':</span> <span class="pre">'Slice',</span> <span class="pre">'1':</span> <span class="pre">'DifferencedTransformer',</span> <span class="pre">'2':</span> <span class="pre">'RollingMeanTransformer',</span> <span class="pre">'3':</span> <span class="pre">'MaxAbsScaler'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'max_generations':</span> <span class="pre">30,</span> <span class="pre">'n_jobs':</span> <span class="pre">'auto',</span> <span class="pre">'random_seed':</span> <span class="pre">321,</span> <span class="pre">'verbose':</span> <span class="pre">1}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">EventRiskForecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.95</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'UnivariateMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'distance_metric':</span> <span class="pre">'euclidean',</span> <span class="pre">'k':</span> <span class="pre">10,</span> <span class="pre">'pointed_method':</span> <span class="pre">'median',</span> <span class="pre">'return_result_windows':</span> <span class="pre">True,</span> <span class="pre">'window':</span> <span class="pre">14}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'fillna':</span> <span class="pre">'pchip',</span> <span class="pre">'transformation_params':</span> <span class="pre">{'0':</span> <span class="pre">{'method':</span> <span class="pre">0.5},</span> <span class="pre">'1':</span> <span class="pre">{},</span> <span class="pre">'2':</span> <span class="pre">{'fixed':</span> <span class="pre">False,</span> <span class="pre">'window':</span> <span class="pre">7},</span> <span class="pre">'3':</span> <span class="pre">{}},</span> <span class="pre">'transformations':</span> <span class="pre">{'0':</span> <span class="pre">'Slice',</span> <span class="pre">'1':</span> <span class="pre">'DifferencedTransformer',</span> <span class="pre">'2':</span> <span class="pre">'RollingMeanTransformer',</span> <span class="pre">'3':</span> <span class="pre">'MaxAbsScaler'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'max_generations':</span> <span class="pre">30,</span> <span class="pre">'n_jobs':</span> <span class="pre">'auto',</span> <span class="pre">'random_seed':</span> <span class="pre">321,</span> <span class="pre">'verbose':</span> <span class="pre">1}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Generate a risk score (0 to 1, but usually close to 0) for a future event exceeding user specified upper or lower bounds.</p>
 <p>Upper and lower limits can be one of four types, and may each be different.
@@ -1260,42 +1268,42 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.predict_historic">
-<span class="sig-name descname"><span class="pre">predict_historic</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.predict_historic" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_historic</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.predict_historic" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.generate_result_windows">
-<span class="sig-name descname"><span class="pre">generate_result_windows</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.generate_result_windows" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate_result_windows</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.generate_result_windows" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.generate_risk_array">
-<span class="sig-name descname"><span class="pre">generate_risk_array</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.generate_risk_array" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate_risk_array</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.generate_risk_array" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.generate_historic_risk_array">
-<span class="sig-name descname"><span class="pre">generate_historic_risk_array</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.generate_historic_risk_array" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate_historic_risk_array</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.generate_historic_risk_array" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.set_limit">
-<span class="sig-name descname"><span class="pre">set_limit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.set_limit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">set_limit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.set_limit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.plot">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.plot" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.plot" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
@@ -1310,7 +1318,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id0">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'event_risk'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['UnivariateMotif',</span> <span class="pre">'MultivariateMotif',</span> <span class="pre">'SectionalMotif',</span> <span class="pre">'ARCH',</span> <span class="pre">'MetricMotif',</span> <span class="pre">'SeasonalityMotif']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">autots_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id0" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'event_risk'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['UnivariateMotif',</span> <span class="pre">'MultivariateMotif',</span> <span class="pre">'SectionalMotif',</span> <span class="pre">'ARCH',</span> <span class="pre">'MetricMotif',</span> <span class="pre">'SeasonalityMotif']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">autots_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id0" title="Link to this definition">¶</a></dt>
 <dd><p>Shortcut for generating model params.</p>
 <p>args specified are those suggested for an otherwise normal AutoTS run</p>
 <dl class="field-list simple">
@@ -1329,13 +1337,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id7">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">generate_historic_risk_array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id7" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">generate_historic_risk_array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id7" title="Link to this definition">¶</a></dt>
 <dd><p>Given a df and a limit, returns a 0/1 array of whether limit was equaled or exceeded.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id8">
-<span class="sig-name descname"><span class="pre">generate_result_windows</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id8" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate_result_windows</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id8" title="Link to this definition">¶</a></dt>
 <dd><p>For event risk forecasting. Params default to class init but can be overridden here.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Returns<span class="colon">:</span></dt>
@@ -1349,13 +1357,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id9">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">generate_risk_array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_windows</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id9" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">generate_risk_array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_windows</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id9" title="Link to this definition">¶</a></dt>
 <dd><p>Given a df and a limit, returns a 0/1 array of whether limit was equaled or exceeded.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id10">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">column_idx</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#838996',</span> <span class="pre">'#c0c0c0',</span> <span class="pre">'#dcdcdc',</span> <span class="pre">'#a9a9a9',</span> <span class="pre">'#808080',</span> <span class="pre">'#989898',</span> <span class="pre">'#808080',</span> <span class="pre">'#757575',</span> <span class="pre">'#696969',</span> <span class="pre">'#c9c0bb',</span> <span class="pre">'#c8c8c8',</span> <span class="pre">'#323232',</span> <span class="pre">'#e5e4e2',</span> <span class="pre">'#778899',</span> <span class="pre">'#4f666a',</span> <span class="pre">'#848482',</span> <span class="pre">'#414a4c',</span> <span class="pre">'#8a7f80',</span> <span class="pre">'#c4c3d0',</span> <span class="pre">'#bebebe',</span> <span class="pre">'#dbd7d2']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">up_low_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#ff4500',</span> <span class="pre">'#ff5349']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#6495ED'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_ylim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.0,</span> <span class="pre">0.5]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(14,</span> <span class="pre">8)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result_windows</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id10" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">column_idx</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#838996',</span> <span class="pre">'#c0c0c0',</span> <span class="pre">'#dcdcdc',</span> <span class="pre">'#a9a9a9',</span> <span class="pre">'#808080',</span> <span class="pre">'#989898',</span> <span class="pre">'#808080',</span> <span class="pre">'#757575',</span> <span class="pre">'#696969',</span> <span class="pre">'#c9c0bb',</span> <span class="pre">'#c8c8c8',</span> <span class="pre">'#323232',</span> <span class="pre">'#e5e4e2',</span> <span class="pre">'#778899',</span> <span class="pre">'#4f666a',</span> <span class="pre">'#848482',</span> <span class="pre">'#414a4c',</span> <span class="pre">'#8a7f80',</span> <span class="pre">'#c4c3d0',</span> <span class="pre">'#bebebe',</span> <span class="pre">'#dbd7d2']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">up_low_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#ff4500',</span> <span class="pre">'#ff5349']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#6495ED'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_ylim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.0,</span> <span class="pre">0.5]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(14,</span> <span class="pre">8)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result_windows</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id10" title="Link to this definition">¶</a></dt>
 <dd><p>Plot a sample of the risk forecast outcomes.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1373,7 +1381,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.EventRiskForecast.plot_eval">
-<span class="sig-name descname"><span class="pre">plot_eval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">column_idx</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#00BFFF']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">up_low_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#ff4500',</span> <span class="pre">'#ff5349']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#6495ED'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_ylim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.0,</span> <span class="pre">0.5]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(14,</span> <span class="pre">8)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.plot_eval" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_eval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">column_idx</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#00BFFF']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">up_low_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#ff4500',</span> <span class="pre">'#ff5349']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#6495ED'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_ylim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.0,</span> <span class="pre">0.5]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(14,</span> <span class="pre">8)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.EventRiskForecast.plot_eval" title="Link to this definition">¶</a></dt>
 <dd><p>Plot a sample of the risk forecast with known value vs risk score.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1392,13 +1400,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id11">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#id11" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#id11" title="Link to this definition">¶</a></dt>
 <dd><p>Returns forecast upper, lower risk probability arrays for input limits.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id12">
-<span class="sig-name descname"><span class="pre">predict_historic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id12" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_historic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id12" title="Link to this definition">¶</a></dt>
 <dd><p>Returns upper, lower risk probability arrays for input limits for the historic data.
 If manual numpy array limits are used, the limits will need to be appropriate shape (for df_train and eval_periods if used)</p>
 <dl class="field-list simple">
@@ -1414,7 +1422,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id13">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">set_limit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id13" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">set_limit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id13" title="Link to this definition">¶</a></dt>
 <dd><p>Handles all limit input styles and returns numpy array.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1435,30 +1443,30 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.extract_result_windows">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">extract_result_windows</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.extract_result_windows" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">extract_result_windows</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.extract_result_windows" title="Link to this definition">¶</a></dt>
 <dd><p>standardize result windows from different models.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.extract_window_index">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">extract_window_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.extract_window_index" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">extract_window_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.extract_window_index" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.set_limit_forecast">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">set_limit_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeasonalNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'lag_1':</span> <span class="pre">28,</span> <span class="pre">'lag_2':</span> <span class="pre">None,</span> <span class="pre">'method':</span> <span class="pre">'median'}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'fillna':</span> <span class="pre">'nearest',</span> <span class="pre">'transformation_params':</span> <span class="pre">{},</span> <span class="pre">'transformations':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'n_jobs':</span> <span class="pre">'auto',</span> <span class="pre">'random_seed':</span> <span class="pre">321,</span> <span class="pre">'verbose':</span> <span class="pre">1}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.set_limit_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">set_limit_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeasonalNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'lag_1':</span> <span class="pre">28,</span> <span class="pre">'lag_2':</span> <span class="pre">None,</span> <span class="pre">'method':</span> <span class="pre">'median'}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'fillna':</span> <span class="pre">'nearest',</span> <span class="pre">'transformation_params':</span> <span class="pre">{},</span> <span class="pre">'transformations':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'n_jobs':</span> <span class="pre">'auto',</span> <span class="pre">'random_seed':</span> <span class="pre">321,</span> <span class="pre">'verbose':</span> <span class="pre">1}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.set_limit_forecast" title="Link to this definition">¶</a></dt>
 <dd><p>Helper function for forecast limits set by forecast algorithms.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.event_forecasting.set_limit_forecast_historic">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">set_limit_forecast_historic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeasonalNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'lag_1':</span> <span class="pre">28,</span> <span class="pre">'lag_2':</span> <span class="pre">None,</span> <span class="pre">'method':</span> <span class="pre">'median'}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'fillna':</span> <span class="pre">'nearest',</span> <span class="pre">'transformation_params':</span> <span class="pre">{},</span> <span class="pre">'transformations':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'n_jobs':</span> <span class="pre">'auto',</span> <span class="pre">'random_seed':</span> <span class="pre">321,</span> <span class="pre">'verbose':</span> <span class="pre">2}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.set_limit_forecast_historic" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.event_forecasting.</span></span><span class="sig-name descname"><span class="pre">set_limit_forecast_historic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeasonalNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'lag_1':</span> <span class="pre">28,</span> <span class="pre">'lag_2':</span> <span class="pre">None,</span> <span class="pre">'method':</span> <span class="pre">'median'}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'fillna':</span> <span class="pre">'nearest',</span> <span class="pre">'transformation_params':</span> <span class="pre">{},</span> <span class="pre">'transformations':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'n_jobs':</span> <span class="pre">'auto',</span> <span class="pre">'random_seed':</span> <span class="pre">321,</span> <span class="pre">'verbose':</span> <span class="pre">2}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.event_forecasting.set_limit_forecast_historic" title="Link to this definition">¶</a></dt>
 <dd><p>Helper function for forecast limits set by forecast algorithms.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.evaluator.metrics">
-<span id="autots-evaluator-metrics-module"></span><h2>autots.evaluator.metrics module<a class="headerlink" href="#module-autots.evaluator.metrics" title="Permalink to this heading">¶</a></h2>
+<span id="autots-evaluator-metrics-module"></span><h2>autots.evaluator.metrics module<a class="headerlink" href="#module-autots.evaluator.metrics" title="Link to this heading">¶</a></h2>
 <p>Tools for calculating forecast errors.</p>
 <dl class="simple">
 <dt>Some common args:</dt><dd><p>A or actual (np.array): actuals ndim 2 (timesteps, series)
@@ -1468,18 +1476,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.array_last_val">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">array_last_val</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.array_last_val" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">array_last_val</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.array_last_val" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.chi_squared_hist_distribution_loss">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">chi_squared_hist_distribution_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.chi_squared_hist_distribution_loss" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">chi_squared_hist_distribution_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.chi_squared_hist_distribution_loss" title="Link to this definition">¶</a></dt>
 <dd><p>Distribution loss, chi-squared distance from histograms.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.containment">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">containment</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lower_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actual</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.containment" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">containment</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lower_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actual</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.containment" title="Link to this definition">¶</a></dt>
 <dd><p>Expects two, 2-D numpy arrays of forecast_length * n series.</p>
 <p>Returns a 1-D array of results in len n series</p>
 <dl class="field-list simple">
@@ -1494,7 +1502,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.contour">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">contour</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.contour" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">contour</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.contour" title="Link to this definition">¶</a></dt>
 <dd><p>A measure of how well the actual and forecast follow the same pattern of change.
 <em>Note:</em> If actual values are unchanging, will match positive changing forecasts.
 This is faster, and because if actuals are a flat line, contour probably isn’t a concern regardless.</p>
@@ -1515,18 +1523,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.default_scaler">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">default_scaler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.default_scaler" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">default_scaler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.default_scaler" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.dwae">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">dwae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.dwae" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">dwae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.dwae" title="Link to this definition">¶</a></dt>
 <dd><p>Direcitonal Weighted Absolute Error, the accuracy of growth or decline relative to most recent data.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.full_metric_evaluation">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">full_metric_evaluation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cumsum_A</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">diff_A</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.full_metric_evaluation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">full_metric_evaluation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cumsum_A</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">diff_A</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.full_metric_evaluation" title="Link to this definition">¶</a></dt>
 <dd><p>Create a pd.DataFrame of metrics per series given actuals, forecast, and precalculated errors.
 There are some extra args which are precomputed metrics for efficiency in loops, don’t worry about them.</p>
 <dl class="field-list simple">
@@ -1542,36 +1550,36 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.kde">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">kde</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actuals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bandwidth</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.kde" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">kde</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actuals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bandwidth</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.kde" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.kde_kl_distance">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">kde_kl_distance</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bandwidth</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.kde_kl_distance" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">kde_kl_distance</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bandwidth</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.kde_kl_distance" title="Link to this definition">¶</a></dt>
 <dd><p>Distribution loss by means of KDE and KL Divergence.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.kl_divergence">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">kl_divergence</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1e-10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.kl_divergence" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">kl_divergence</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1e-10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.kl_divergence" title="Link to this definition">¶</a></dt>
 <dd><p>Compute KL Divergence between two distributions.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.linearity">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">linearity</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.linearity" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">linearity</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.linearity" title="Link to this definition">¶</a></dt>
 <dd><p>Score perecentage of a np.array with linear progression, along the index (0) axis.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.mae">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ae</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mae" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ae</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mae" title="Link to this definition">¶</a></dt>
 <dd><p>Accepting abs error already calculated</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.mda">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mda</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mda" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mda</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mda" title="Link to this definition">¶</a></dt>
 <dd><p>A measure of how well the actual and forecast follow the same pattern of change.
 Expects two, 2-D numpy arrays of forecast_length * n series
 Returns a 1-D array of results in len n series</p>
@@ -1589,7 +1597,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.mean_absolute_differential_error">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mean_absolute_differential_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mean_absolute_differential_error" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mean_absolute_differential_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mean_absolute_differential_error" title="Link to this definition">¶</a></dt>
 <dd><p>Expects two, 2-D numpy arrays of forecast_length * n series.</p>
 <p>Returns a 1-D array of results in len n series</p>
 <dl class="field-list simple">
@@ -1612,7 +1620,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.mean_absolute_error">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mean_absolute_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mean_absolute_error" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mean_absolute_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mean_absolute_error" title="Link to this definition">¶</a></dt>
 <dd><p>Expects two, 2-D numpy arrays of forecast_length * n series.</p>
 <p>Returns a 1-D array of results in len n series</p>
 <dl class="field-list simple">
@@ -1627,13 +1635,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.medae">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">medae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.medae" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">medae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.medae" title="Link to this definition">¶</a></dt>
 <dd><p>Accepting abs error already calculated</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.median_absolute_error">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">median_absolute_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.median_absolute_error" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">median_absolute_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.median_absolute_error" title="Link to this definition">¶</a></dt>
 <dd><p>Expects two, 2-D numpy arrays of forecast_length * n series.</p>
 <p>Returns a 1-D array of results in len n series</p>
 <dl class="field-list simple">
@@ -1648,7 +1656,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.mlvb">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mlvb</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mlvb" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mlvb</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mlvb" title="Link to this definition">¶</a></dt>
 <dd><p>Mean last value baseline, the % difference of forecast vs last value naive forecast.
 Does poorly with near-zero values.</p>
 <dl class="field-list simple">
@@ -1664,14 +1672,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.mqae">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mqae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.85</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mqae" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">mqae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.85</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.mqae" title="Link to this definition">¶</a></dt>
 <dd><p>Return the mean of errors less than q quantile of the errors per series.
 np.nans count as largest values, and so are removed as part of the &gt; q group.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.msle">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">msle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">full_errors</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">le</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.msle" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">msle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">full_errors</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">le</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.msle" title="Link to this definition">¶</a></dt>
 <dd><p>input is array of y_pred - y_true to over-penalize underestimate.
 Use instead y_true - y_pred to over-penalize overestimate.
 AE used here for the log just to avoid divide by zero warnings (values aren’t used either way)</p>
@@ -1679,43 +1687,43 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.numpy_ffill">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">numpy_ffill</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.numpy_ffill" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">numpy_ffill</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.numpy_ffill" title="Link to this definition">¶</a></dt>
 <dd><p>Fill np.nan forward down the zero axis.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.oda">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">oda</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.oda" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">oda</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.oda" title="Link to this definition">¶</a></dt>
 <dd><p>Origin Directional Accuracy, the accuracy of growth or decline relative to most recent data.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.pinball_loss">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">pinball_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.pinball_loss" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">pinball_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.pinball_loss" title="Link to this definition">¶</a></dt>
 <dd><p>Bigger is bad-er.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.precomp_wasserstein">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">precomp_wasserstein</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cumsum_A</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.precomp_wasserstein" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">precomp_wasserstein</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cumsum_A</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.precomp_wasserstein" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.qae">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">qae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.qae" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">qae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.qae" title="Link to this definition">¶</a></dt>
 <dd><p>Return the q quantile of the errors per series.
 np.nans count as smallest values and will push more values into the exclusion group.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.rmse">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">rmse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sqe</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.rmse" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">rmse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sqe</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.rmse" title="Link to this definition">¶</a></dt>
 <dd><p>Accepting squared error already calculated</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.root_mean_square_error">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">root_mean_square_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.root_mean_square_error" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">root_mean_square_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.root_mean_square_error" title="Link to this definition">¶</a></dt>
 <dd><p>Expects two, 2-D numpy arrays of forecast_length * n series.</p>
 <p>Returns a 1-D array of results in len n series</p>
 <dl class="field-list simple">
@@ -1730,7 +1738,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.rps">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">rps</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">predictions</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observed</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.rps" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">rps</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">predictions</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observed</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.rps" title="Link to this definition">¶</a></dt>
 <dd><p>Vectorized version of Ranked Probability Score.
 A lower value is a better score.
 From: Colin Catlin, <a class="reference external" href="https://syllepsis.live/2022/01/22/ranked-probability-score-in-python/">https://syllepsis.live/2022/01/22/ranked-probability-score-in-python/</a></p>
@@ -1746,7 +1754,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.scaled_pinball_loss">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">scaled_pinball_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.scaled_pinball_loss" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">scaled_pinball_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.scaled_pinball_loss" title="Link to this definition">¶</a></dt>
 <dd><p>Scaled pinball loss.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1762,25 +1770,25 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.smape">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">smape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.smape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">smape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ae</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.smape" title="Link to this definition">¶</a></dt>
 <dd><p>Accepting abs error already calculated</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.smoothness">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">smoothness</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.smoothness" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">smoothness</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.smoothness" title="Link to this definition">¶</a></dt>
 <dd><p>A gradient measure of linearity, where 0 is linear and larger values are more volatile.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.spl">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">spl</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">precomputed_spl</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.spl" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">spl</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">precomputed_spl</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.spl" title="Link to this definition">¶</a></dt>
 <dd><p>Accepting most of it already calculated</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.symmetric_mean_absolute_percentage_error">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">symmetric_mean_absolute_percentage_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.symmetric_mean_absolute_percentage_error" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">symmetric_mean_absolute_percentage_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.symmetric_mean_absolute_percentage_error" title="Link to this definition">¶</a></dt>
 <dd><p>Expect two, 2-D numpy arrays of forecast_length * n series.
 Allows NaN in actuals, and corresponding NaN in forecast, but not unmatched NaN in forecast
 Also doesn’t like zeroes in either forecast or actual - results in poor error value even if forecast is accurate</p>
@@ -1799,7 +1807,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.threshold_loss">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">threshold_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">penalty_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.threshold_loss" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">threshold_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">penalty_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.threshold_loss" title="Link to this definition">¶</a></dt>
 <dd><p>Run once for overestimate then again for underestimate. Add both for combined view.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1814,31 +1822,31 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.unsorted_wasserstein">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">unsorted_wasserstein</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.unsorted_wasserstein" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">unsorted_wasserstein</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.unsorted_wasserstein" title="Link to this definition">¶</a></dt>
 <dd><p>Also known as earth moving distance.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.metrics.wasserstein">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">wasserstein</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.wasserstein" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.metrics.</span></span><span class="sig-name descname"><span class="pre">wasserstein</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">F</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.metrics.wasserstein" title="Link to this definition">¶</a></dt>
 <dd><p>This version has sorting, which is perhaps less relevant on average than the unsorted.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.evaluator.validation">
-<span id="autots-evaluator-validation-module"></span><h2>autots.evaluator.validation module<a class="headerlink" href="#module-autots.evaluator.validation" title="Permalink to this heading">¶</a></h2>
+<span id="autots-evaluator-validation-module"></span><h2>autots.evaluator.validation module<a class="headerlink" href="#module-autots.evaluator.validation" title="Link to this heading">¶</a></h2>
 <p>Extracted from auto_ts.py, the functions to create validation segments.</p>
 <p>Warning, these are used in AMFM, possibly other places. Avoid modification of function structures, if possible.</p>
 <p>Created on Mon Jan 16 11:36:01 2023</p>
 <p>&#64;author: Colin</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.validation.extract_seasonal_val_periods">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.validation.</span></span><span class="sig-name descname"><span class="pre">extract_seasonal_val_periods</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.validation.extract_seasonal_val_periods" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.validation.</span></span><span class="sig-name descname"><span class="pre">extract_seasonal_val_periods</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.validation.extract_seasonal_val_periods" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.validation.generate_validation_indices">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.validation.</span></span><span class="sig-name descname"><span class="pre">generate_validation_indices</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_wide_numeric</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preclean</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.validation.generate_validation_indices" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.validation.</span></span><span class="sig-name descname"><span class="pre">generate_validation_indices</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_wide_numeric</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preclean</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.validation.generate_validation_indices" title="Link to this definition">¶</a></dt>
 <dd><p>generate validation indices (equals num_validations + 1 as includes initial eval).</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1856,13 +1864,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.evaluator.validation.validate_num_validations">
-<span class="sig-prename descclassname"><span class="pre">autots.evaluator.validation.</span></span><span class="sig-name descname"><span class="pre">validate_num_validations</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_wide_numeric</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.validation.validate_num_validations" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.evaluator.validation.</span></span><span class="sig-name descname"><span class="pre">validate_num_validations</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_wide_numeric</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.evaluator.validation.validate_num_validations" title="Link to this definition">¶</a></dt>
 <dd><p>Check how many validations are possible given the length of the data. Beyond initial eval split which is always assumed.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.evaluator">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.evaluator" title="Permalink to this heading">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.evaluator" title="Link to this heading">¶</a></h2>
 <p>Model Evaluators</p>
 </section>
 </section>
@@ -1957,21 +1965,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/source/autots.html b/docs/build/html/source/autots.html
index 3b33f7fc..03027ce0 100644
--- a/docs/build/html/source/autots.html
+++ b/docs/build/html/source/autots.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="../">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>autots package &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
-    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/doctools.js"></script>
-    <script src="../_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css?v=a4fa0645" />
+    <script src="../_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="../_static/doctools.js?v=888ff710"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
     <link rel="next" title="autots.datasets package" href="autots.datasets.html" />
@@ -33,9 +41,9 @@
           <div class="body" role="main">
             
   <section id="autots-package">
-<h1>autots package<a class="headerlink" href="#autots-package" title="Permalink to this heading">¶</a></h1>
+<h1>autots package<a class="headerlink" href="#autots-package" title="Link to this heading">¶</a></h1>
 <section id="subpackages">
-<h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to this heading">¶</a></h2>
+<h2>Subpackages<a class="headerlink" href="#subpackages" title="Link to this heading">¶</a></h2>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="autots.datasets.html">autots.datasets package</a><ul>
@@ -1442,16 +1450,16 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </div>
 </section>
 <section id="module-autots">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots" title="Permalink to this heading">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots" title="Link to this heading">¶</a></h2>
 <p>Automated Time Series Model Selection for Python</p>
 <p><a class="reference external" href="https://github.com/winedarksea/AutoTS">https://github.com/winedarksea/AutoTS</a></p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.AnomalyDetector">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">AnomalyDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zscore'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'transformation_params':</span> <span class="pre">{0:</span> <span class="pre">{'datepart_method':</span> <span class="pre">'simple_3',</span> <span class="pre">'regression_model':</span> <span class="pre">{'model':</span> <span class="pre">'ElasticNet',</span> <span class="pre">'model_params':</span> <span class="pre">{}}}},</span> <span class="pre">'transformations':</span> <span class="pre">{0:</span> <span class="pre">'DatepartRegression'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">isolated_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">AnomalyDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zscore'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'transformation_params':</span> <span class="pre">{0:</span> <span class="pre">{'datepart_method':</span> <span class="pre">'simple_3',</span> <span class="pre">'regression_model':</span> <span class="pre">{'model':</span> <span class="pre">'ElasticNet',</span> <span class="pre">'model_params':</span> <span class="pre">{}}}},</span> <span class="pre">'transformations':</span> <span class="pre">{0:</span> <span class="pre">'DatepartRegression'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">isolated_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AnomalyDetector.detect">
-<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.detect" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.detect" title="Link to this definition">¶</a></dt>
 <dd><p>All will return -1 for anomalies.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1465,18 +1473,18 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AnomalyDetector.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AnomalyDetector.fit_anomaly_classifier">
-<span class="sig-name descname"><span class="pre">fit_anomaly_classifier</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.fit_anomaly_classifier" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_anomaly_classifier</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.fit_anomaly_classifier" title="Link to this definition">¶</a></dt>
 <dd><p>Fit a model to predict if a score is an anomaly.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AnomalyDetector.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate random new parameter combinations.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1487,12 +1495,12 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AnomalyDetector.plot">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.plot" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.plot" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AnomalyDetector.score_to_anomaly">
-<span class="sig-name descname"><span class="pre">score_to_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scores</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.score_to_anomaly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">score_to_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scores</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AnomalyDetector.score_to_anomaly" title="Link to this definition">¶</a></dt>
 <dd><p>A DecisionTree model, used as models are nonstandard (and nonparametric).</p>
 </dd></dl>
 
@@ -1500,7 +1508,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.AutoTS">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">AutoTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_generations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_template</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'General+Random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_weighting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'containment_weighting':</span> <span class="pre">0,</span> <span class="pre">'contour_weighting':</span> <span class="pre">0.01,</span> <span class="pre">'imle_weighting':</span> <span class="pre">0,</span> <span class="pre">'made_weighting':</span> <span class="pre">0.05,</span> <span class="pre">'mae_weighting':</span> <span class="pre">2,</span> <span class="pre">'mage_weighting':</span> <span class="pre">0,</span> <span class="pre">'mle_weighting':</span> <span class="pre">0,</span> <span class="pre">'oda_weighting':</span> <span class="pre">0.001,</span> <span class="pre">'rmse_weighting':</span> <span class="pre">2,</span> <span class="pre">'runtime_weighting':</span> <span class="pre">0.01,</span> <span class="pre">'smape_weighting':</span> <span class="pre">5,</span> <span class="pre">'spl_weighting':</span> <span class="pre">3,</span> <span class="pre">'wasserstein_weighting':</span> <span class="pre">0.01}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_data_older_than_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_validate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.15</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'backwards'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_leading_zeroes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preclean</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_interrupt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">generation_timeout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">AutoTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_generations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_template</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'General+Random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_weighting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'containment_weighting':</span> <span class="pre">0,</span> <span class="pre">'contour_weighting':</span> <span class="pre">0.01,</span> <span class="pre">'imle_weighting':</span> <span class="pre">0,</span> <span class="pre">'made_weighting':</span> <span class="pre">0.05,</span> <span class="pre">'mae_weighting':</span> <span class="pre">2,</span> <span class="pre">'mage_weighting':</span> <span class="pre">0,</span> <span class="pre">'mle_weighting':</span> <span class="pre">0,</span> <span class="pre">'oda_weighting':</span> <span class="pre">0.001,</span> <span class="pre">'rmse_weighting':</span> <span class="pre">2,</span> <span class="pre">'runtime_weighting':</span> <span class="pre">0.01,</span> <span class="pre">'smape_weighting':</span> <span class="pre">5,</span> <span class="pre">'spl_weighting':</span> <span class="pre">3,</span> <span class="pre">'wasserstein_weighting':</span> <span class="pre">0.01}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_data_older_than_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_validate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.15</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'backwards'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_leading_zeroes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preclean</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_interrupt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">generation_timeout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Automate time series modeling using a genetic algorithm.</p>
 <dl class="field-list simple">
@@ -1595,7 +1603,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </dl>
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.best_model">
-<span class="sig-name descname"><span class="pre">best_model</span></span><a class="headerlink" href="#autots.AutoTS.best_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model</span></span><a class="headerlink" href="#autots.AutoTS.best_model" title="Link to this definition">¶</a></dt>
 <dd><p>DataFrame containing template for the best ranked model</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1606,7 +1614,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.best_model_name">
-<span class="sig-name descname"><span class="pre">best_model_name</span></span><a class="headerlink" href="#autots.AutoTS.best_model_name" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_name</span></span><a class="headerlink" href="#autots.AutoTS.best_model_name" title="Link to this definition">¶</a></dt>
 <dd><p>model name</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1617,7 +1625,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.best_model_params">
-<span class="sig-name descname"><span class="pre">best_model_params</span></span><a class="headerlink" href="#autots.AutoTS.best_model_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_params</span></span><a class="headerlink" href="#autots.AutoTS.best_model_params" title="Link to this definition">¶</a></dt>
 <dd><p>model params</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1628,7 +1636,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.best_model_transformation_params">
-<span class="sig-name descname"><span class="pre">best_model_transformation_params</span></span><a class="headerlink" href="#autots.AutoTS.best_model_transformation_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_transformation_params</span></span><a class="headerlink" href="#autots.AutoTS.best_model_transformation_params" title="Link to this definition">¶</a></dt>
 <dd><p>transformation parameters</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1639,7 +1647,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.best_model_ensemble">
-<span class="sig-name descname"><span class="pre">best_model_ensemble</span></span><a class="headerlink" href="#autots.AutoTS.best_model_ensemble" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_ensemble</span></span><a class="headerlink" href="#autots.AutoTS.best_model_ensemble" title="Link to this definition">¶</a></dt>
 <dd><p>Ensemble type int id</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1650,7 +1658,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.regression_check">
-<span class="sig-name descname"><span class="pre">regression_check</span></span><a class="headerlink" href="#autots.AutoTS.regression_check" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">regression_check</span></span><a class="headerlink" href="#autots.AutoTS.regression_check" title="Link to this definition">¶</a></dt>
 <dd><p>If True, the best_model uses an input ‘User’ future_regressor</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1661,7 +1669,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.df_wide_numeric">
-<span class="sig-name descname"><span class="pre">df_wide_numeric</span></span><a class="headerlink" href="#autots.AutoTS.df_wide_numeric" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">df_wide_numeric</span></span><a class="headerlink" href="#autots.AutoTS.df_wide_numeric" title="Link to this definition">¶</a></dt>
 <dd><p>dataframe containing shaped final data, will include preclean</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1672,7 +1680,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.initial_results.model_results">
-<span class="sig-prename descclassname"><span class="pre">initial_results.</span></span><span class="sig-name descname"><span class="pre">model_results</span></span><a class="headerlink" href="#autots.AutoTS.initial_results.model_results" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">initial_results.</span></span><span class="sig-name descname"><span class="pre">model_results</span></span><a class="headerlink" href="#autots.AutoTS.initial_results.model_results" title="Link to this definition">¶</a></dt>
 <dd><p>contains a collection of result metrics</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1683,7 +1691,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.AutoTS.score_per_series">
-<span class="sig-name descname"><span class="pre">score_per_series</span></span><a class="headerlink" href="#autots.AutoTS.score_per_series" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">score_per_series</span></span><a class="headerlink" href="#autots.AutoTS.score_per_series" title="Link to this definition">¶</a></dt>
 <dd><p>generated score of metrics given per input series, if horizontal ensembles</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
@@ -1719,7 +1727,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.back_forecast">
-<span class="sig-name descname"><span class="pre">back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tail</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.back_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tail</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.back_forecast" title="Link to this definition">¶</a></dt>
 <dd><p>Create forecasts for the historical training data, ie. backcast or back forecast. OUT OF SAMPLE</p>
 <p>This actually forecasts on historical data, these are not fit model values as are often returned by other packages.
 As such, this will be slower, but more representative of real world model performance.
@@ -1736,18 +1744,18 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.best_model_per_series_mape">
-<span class="sig-name descname"><span class="pre">best_model_per_series_mape</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.best_model_per_series_mape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_per_series_mape</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.best_model_per_series_mape" title="Link to this definition">¶</a></dt>
 <dd><p>This isn’t quite classic mape but is a percentage mean error intended for quick visuals not final statistics (see model.results()).</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.best_model_per_series_score">
-<span class="sig-name descname"><span class="pre">best_model_per_series_score</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.best_model_per_series_score" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">best_model_per_series_score</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.best_model_per_series_score" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.diagnose_params">
-<span class="sig-name descname"><span class="pre">diagnose_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'runtime'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">waterfall_plots</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.diagnose_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">diagnose_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'runtime'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">waterfall_plots</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.diagnose_params" title="Link to this definition">¶</a></dt>
 <dd><p>Attempt to explain params causing measured outcomes using shap and linear regression coefficients.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1761,20 +1769,20 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.expand_horizontal">
-<span class="sig-name descname"><span class="pre">expand_horizontal</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.expand_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">expand_horizontal</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.expand_horizontal" title="Link to this definition">¶</a></dt>
 <dd><p>Enables expanding horizontal models trained on a subset to full data.
 Reruns template models and generates new template.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.export_best_model">
-<span class="sig-name descname"><span class="pre">export_best_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.export_best_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">export_best_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.export_best_model" title="Link to this definition">¶</a></dt>
 <dd><p>Basically the same as export_template but only ever the one best model.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.export_template">
-<span class="sig-name descname"><span class="pre">export_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'best'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">40</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_results</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unpack_ensembles</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_metrics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['smape',</span> <span class="pre">'spl']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_metrics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.export_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">export_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'best'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">40</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_per_model_class</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_results</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unpack_ensembles</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_metrics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['smape',</span> <span class="pre">'spl']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_metrics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.export_template" title="Link to this definition">¶</a></dt>
 <dd><p>Export top results as a reusable template.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1796,7 +1804,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.failure_rate">
-<span class="sig-name descname"><span class="pre">failure_rate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'initial'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.failure_rate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">failure_rate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'initial'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.failure_rate" title="Link to this definition">¶</a></dt>
 <dd><p>Return fraction of models passing with exceptions.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1810,7 +1818,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_indexes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_indexes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1835,13 +1843,13 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.fit_data" title="Link to this definition">¶</a></dt>
 <dd><p>Part of the setup that involves fitting the initial data but not running any models.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.get_metric_corr">
-<span class="sig-name descname"><span class="pre">get_metric_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">percent_best</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.get_metric_corr" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_metric_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">percent_best</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.get_metric_corr" title="Link to this definition">¶</a></dt>
 <dd><p>Returns a dataframe of correlation among evaluation metrics across evaluations.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1852,24 +1860,24 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Randomly generate new parameters for the class.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.horizontal_per_generation">
-<span class="sig-name descname"><span class="pre">horizontal_per_generation</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.horizontal_per_generation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">horizontal_per_generation</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.horizontal_per_generation" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.horizontal_to_df">
-<span class="sig-name descname"><span class="pre">horizontal_to_df</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.horizontal_to_df" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">horizontal_to_df</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.horizontal_to_df" title="Link to this definition">¶</a></dt>
 <dd><p>helper function for plotting.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.import_best_model">
-<span class="sig-name descname"><span class="pre">import_best_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">import_target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enforce_model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.import_best_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">import_best_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">import_target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enforce_model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.import_best_model" title="Link to this definition">¶</a></dt>
 <dd><p>Load a best model, overriding any existing setting.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1880,7 +1888,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.import_results">
-<span class="sig-name descname"><span class="pre">import_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.import_results" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">import_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.import_results" title="Link to this definition">¶</a></dt>
 <dd><p>Add results from another run on the same data.</p>
 <p>Input can be filename with .csv or .pickle.
 or can be a DataFrame of model results or a full TemplateEvalObject</p>
@@ -1888,7 +1896,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.import_template">
-<span class="sig-name descname"><span class="pre">import_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'add_on'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enforce_model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_horizontal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_validation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.import_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">import_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'add_on'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enforce_model_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_horizontal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_validation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.import_template" title="Link to this definition">¶</a></dt>
 <dd><p>Import a previously exported template of model parameters.
 Must be done before the AutoTS object is .fit().</p>
 <dl class="field-list simple">
@@ -1908,36 +1916,36 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.list_failed_model_types">
-<span class="sig-name descname"><span class="pre">list_failed_model_types</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.list_failed_model_types" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">list_failed_model_types</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.list_failed_model_types" title="Link to this definition">¶</a></dt>
 <dd><p>Return a list of model types (ie ETS, LastValueNaive) that failed.
 If all had at least one success, then return an empty list.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.load_template">
-<span class="sig-name descname"><span class="pre">load_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.load_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">load_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.load_template" title="Link to this definition">¶</a></dt>
 <dd><p>Helper funciton for just loading the file part of import_template.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.mosaic_to_df">
-<span class="sig-name descname"><span class="pre">mosaic_to_df</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.mosaic_to_df" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">mosaic_to_df</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.mosaic_to_df" title="Link to this definition">¶</a></dt>
 <dd><p>Helper function to create a readable df of models in mosaic.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.parse_best_model">
-<span class="sig-name descname"><span class="pre">parse_best_model</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.parse_best_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">parse_best_model</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.parse_best_model" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_back_forecast">
-<span class="sig-name descname"><span class="pre">plot_back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_back_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_back_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_back_forecast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_backforecast">
-<span class="sig-name descname"><span class="pre">plot_backforecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">facecolor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'black'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper</span> <span class="pre">left'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_backforecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_backforecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_splits</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">facecolor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'black'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper</span> <span class="pre">left'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_backforecast" title="Link to this definition">¶</a></dt>
 <dd><p>Plot the historical data and fit forecast on historic. Out of sample in chunks = forecast_length by default.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1954,7 +1962,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_generation_loss">
-<span class="sig-name descname"><span class="pre">plot_generation_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Single</span> <span class="pre">Model</span> <span class="pre">Accuracy</span> <span class="pre">Gain</span> <span class="pre">Over</span> <span class="pre">Generations'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_generation_loss" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_generation_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Single</span> <span class="pre">Model</span> <span class="pre">Accuracy</span> <span class="pre">Gain</span> <span class="pre">Over</span> <span class="pre">Generations'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_generation_loss" title="Link to this definition">¶</a></dt>
 <dd><p>Plot improvement in accuracy over generations.
 Note: this is only “one size fits all” accuracy and
 doesn’t account for the benefits seen for ensembling.</p>
@@ -1967,7 +1975,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_horizontal">
-<span class="sig-name descname"><span class="pre">plot_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Model</span> <span class="pre">Types</span> <span class="pre">Chosen</span> <span class="pre">by</span> <span class="pre">Series'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Model</span> <span class="pre">Types</span> <span class="pre">Chosen</span> <span class="pre">by</span> <span class="pre">Series'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_horizontal" title="Link to this definition">¶</a></dt>
 <dd><p>Simple plot to visualize assigned series: models.</p>
 <p>Note that for ‘mosaic’ ensembles, it only plots the type of the most common model_id for that series, or the first if all are mode.</p>
 <dl class="field-list simple">
@@ -1982,19 +1990,19 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_horizontal_model_count">
-<span class="sig-name descname"><span class="pre">plot_horizontal_model_count</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">color_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">top_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Most</span> <span class="pre">Frequently</span> <span class="pre">Chosen</span> <span class="pre">Models'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_horizontal_model_count" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_horizontal_model_count</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">color_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">top_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Most</span> <span class="pre">Frequently</span> <span class="pre">Chosen</span> <span class="pre">Models'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_horizontal_model_count" title="Link to this definition">¶</a></dt>
 <dd><p>Plots most common models. Does not factor in nested in non-horizontal Ensembles.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_horizontal_per_generation">
-<span class="sig-name descname"><span class="pre">plot_horizontal_per_generation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Horizontal</span> <span class="pre">Ensemble</span> <span class="pre">Accuracy</span> <span class="pre">Gain</span> <span class="pre">(first</span> <span class="pre">eval</span> <span class="pre">sample</span> <span class="pre">only)'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_horizontal_per_generation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_horizontal_per_generation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Horizontal</span> <span class="pre">Ensemble</span> <span class="pre">Accuracy</span> <span class="pre">Gain</span> <span class="pre">(first</span> <span class="pre">eval</span> <span class="pre">sample</span> <span class="pre">only)'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_horizontal_per_generation" title="Link to this definition">¶</a></dt>
 <dd><p>Plot how well the horizontal ensembles would do after each new generation. Slow.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_horizontal_transformers">
-<span class="sig-name descname"><span class="pre">plot_horizontal_transformers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'transformers'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_horizontal_transformers" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_horizontal_transformers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'transformers'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_horizontal_transformers" title="Link to this definition">¶</a></dt>
 <dd><p>Simple plot to visualize transformers used.
 Note this doesn’t capture transformers nested in simple ensembles.</p>
 <dl class="field-list simple">
@@ -2010,7 +2018,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_metric_corr">
-<span class="sig-name descname"><span class="pre">plot_metric_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percent_best</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_metric_corr" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_metric_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percent_best</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_metric_corr" title="Link to this definition">¶</a></dt>
 <dd><p>Plot correlation in results among metrics.
 The metrics that are highly correlated are those that mostly the unscaled ones</p>
 <dl class="field-list simple">
@@ -2025,7 +2033,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_per_series_error">
-<span class="sig-name descname"><span class="pre">plot_per_series_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Top</span> <span class="pre">Series</span> <span class="pre">Contributing</span> <span class="pre">Score</span> <span class="pre">Error'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_clip</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_per_series_error" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_per_series_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Top</span> <span class="pre">Series</span> <span class="pre">Contributing</span> <span class="pre">Score</span> <span class="pre">Error'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_clip</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_per_series_error" title="Link to this definition">¶</a></dt>
 <dd><p>Plot which series are contributing most to error (Score) of final model. Avg of validations for best_model</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2045,7 +2053,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_per_series_mape">
-<span class="sig-name descname"><span class="pre">plot_per_series_mape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_per_series_mape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_per_series_mape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_per_series_mape" title="Link to this definition">¶</a></dt>
 <dd><p>Plot which series are contributing most to SMAPE of final model. Avg of validations for best_model</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2064,19 +2072,19 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_per_series_smape">
-<span class="sig-name descname"><span class="pre">plot_per_series_smape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_per_series_smape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_per_series_smape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_name_chars</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'#ff9912'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(12,</span> <span class="pre">4)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bar'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_per_series_smape" title="Link to this definition">¶</a></dt>
 <dd><p>To be backwards compatible, not necessarily maintained, plot_per_series_mape is to be preferred.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_transformer_failure_rate">
-<span class="sig-name descname"><span class="pre">plot_transformer_failure_rate</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_transformer_failure_rate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_transformer_failure_rate</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_transformer_failure_rate" title="Link to this definition">¶</a></dt>
 <dd><p>Failure Rate per Transformer type (ignoring ensembles), failure may be due to other model or transformer.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.plot_validations">
-<span class="sig-name descname"><span class="pre">plot_validations</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">end_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compare_horizontal</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.35</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkred'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">end_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#A2AD9C'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_validations" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_validations</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">end_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compare_horizontal</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.35</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkred'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">end_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#A2AD9C'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.plot_validations" title="Link to this definition">¶</a></dt>
 <dd><p>Similar to plot_backforecast but using the model’s validation segments specifically. Must reforecast.
 Saves results to self.validation_forecasts and caches. Set that to None to force rerun otherwise it uses stored (when models is the same).
 ‘chosen’ refers to best_model_id, the model chosen to run for predict
@@ -2101,7 +2109,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hierarchy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hierarchy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <p>If using a model from update_fit list, with no ensembling, underlying model will not be retrained when used as below, with a single prediction interval:
 This designed for high speed forecasting. Full retraining is best when there is sufficient time.
@@ -2144,7 +2152,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.results">
-<span class="sig-name descname"><span class="pre">results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'initial'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.results" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'initial'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.results" title="Link to this definition">¶</a></dt>
 <dd><p>Convenience function to return tested models table.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2155,25 +2163,25 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.retrieve_validation_forecasts">
-<span class="sig-name descname"><span class="pre">retrieve_validation_forecasts</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compare_horizontal</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeriesID'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interval_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'PredictionInterval'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.retrieve_validation_forecasts" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">retrieve_validation_forecasts</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compare_horizontal</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeriesID'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interval_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'PredictionInterval'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.retrieve_validation_forecasts" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.save_template">
-<span class="sig-name descname"><span class="pre">save_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">export_template</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.save_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">save_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">export_template</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.save_template" title="Link to this definition">¶</a></dt>
 <dd><p>Helper function for the save part of export_template.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.AutoTS.validation_agg">
-<span class="sig-name descname"><span class="pre">validation_agg</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.validation_agg" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">validation_agg</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.AutoTS.validation_agg" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.Cassandra">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">Cassandra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preprocessing_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaling</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BaseScaler'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts_intervention</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonalities</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['common_fourier']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_interaction_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_intervention</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate_feature</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressors_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">randomwalk_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_standin</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_anomaly_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'Model':</span> <span class="pre">'LastValueNaive',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_colinearity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.998</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_multicolinearity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">Cassandra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preprocessing_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaling</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BaseScaler'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts_intervention</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonalities</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['common_fourier']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_interaction_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_intervention</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate_feature</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressors_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">randomwalk_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_standin</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_anomaly_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'Model':</span> <span class="pre">'LastValueNaive',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_colinearity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.998</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_multicolinearity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="autots.models.html#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Explainable decomposition-based forecasting with advanced trend modeling and preprocessing.</p>
 <p>Tunc etiam fatis aperit Cassandra futuris
@@ -2207,68 +2215,68 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.holiday_detector.dates_to_holidays">
-<span class="sig-prename descclassname"><span class="pre">holiday_detector.</span></span><span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.holiday_detector.dates_to_holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">holiday_detector.</span></span><span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.holiday_detector.dates_to_holidays" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.create_forecast_index">
-<span class="sig-name descname"><span class="pre">create_forecast_index</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.create_forecast_index" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">create_forecast_index</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.create_forecast_index" title="Link to this definition">¶</a></dt>
 <dd><p>after .fit, can be used to create index of prediction</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.plot_forecast">
-<span class="sig-name descname"><span class="pre">plot_forecast</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.plot_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_forecast</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.plot_forecast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.plot_components">
-<span class="sig-name descname"><span class="pre">plot_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.plot_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.plot_components" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.plot_trend">
-<span class="sig-name descname"><span class="pre">plot_trend</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.plot_trend" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_trend</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.plot_trend" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.get_new_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.return_components">
-<span class="sig-name descname"><span class="pre">return_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.return_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">return_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.return_components" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..anomaly_detector.anomalies">
-<span class="sig-prename descclassname"><span class="pre">.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">anomalies</span></span><a class="headerlink" href="#autots.Cassandra..anomaly_detector.anomalies" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">anomalies</span></span><a class="headerlink" href="#autots.Cassandra..anomaly_detector.anomalies" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..anomaly_detector.scores">
-<span class="sig-prename descclassname"><span class="pre">.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">scores</span></span><a class="headerlink" href="#autots.Cassandra..anomaly_detector.scores" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">scores</span></span><a class="headerlink" href="#autots.Cassandra..anomaly_detector.scores" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..holiday_count">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">holiday_count</span></span><a class="headerlink" href="#autots.Cassandra..holiday_count" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">holiday_count</span></span><a class="headerlink" href="#autots.Cassandra..holiday_count" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..holidays">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">holidays</span></span><a class="headerlink" href="#autots.Cassandra..holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">holidays</span></span><a class="headerlink" href="#autots.Cassandra..holidays" title="Link to this definition">¶</a></dt>
 <dd><dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>series flags, holiday detector only</p>
@@ -2278,7 +2286,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..params">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">params</span></span><a class="headerlink" href="#autots.Cassandra..params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">params</span></span><a class="headerlink" href="#autots.Cassandra..params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
@@ -2288,94 +2296,94 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..x_array">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">x_array</span></span><a class="headerlink" href="#autots.Cassandra..x_array" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">x_array</span></span><a class="headerlink" href="#autots.Cassandra..x_array" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..predict_x_array">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">predict_x_array</span></span><a class="headerlink" href="#autots.Cassandra..predict_x_array" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">predict_x_array</span></span><a class="headerlink" href="#autots.Cassandra..predict_x_array" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..trend_train">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">trend_train</span></span><a class="headerlink" href="#autots.Cassandra..trend_train" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">trend_train</span></span><a class="headerlink" href="#autots.Cassandra..trend_train" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.Cassandra..predicted_trend">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">predicted_trend</span></span><a class="headerlink" href="#autots.Cassandra..predicted_trend" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">predicted_trend</span></span><a class="headerlink" href="#autots.Cassandra..predicted_trend" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.analyze_trend">
-<span class="sig-name descname"><span class="pre">analyze_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">slope</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">index</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.analyze_trend" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">analyze_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">slope</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">index</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.analyze_trend" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.auto_fit">
-<span class="sig-name descname"><span class="pre">auto_fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.auto_fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">auto_fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.auto_fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.base_scaler">
-<span class="sig-name descname"><span class="pre">base_scaler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.base_scaler" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">base_scaler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.base_scaler" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.compare_actual_components">
-<span class="sig-name descname"><span class="pre">compare_actual_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.compare_actual_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">compare_actual_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.compare_actual_components" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.create_t">
-<span class="sig-name descname"><span class="pre">create_t</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.create_t" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">create_t</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.create_t" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.cross_validate">
-<span class="sig-name descname"><span class="pre">cross_validate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.cross_validate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">cross_validate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.cross_validate" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.feature_importance">
-<span class="sig-name descname"><span class="pre">feature_importance</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.feature_importance" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">feature_importance</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.feature_importance" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id0">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical_groups</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id0" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical_groups</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id0" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_transformations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_history</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_transformations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_history</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id1">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id1" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id1" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.next_fit">
-<span class="sig-name descname"><span class="pre">next_fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.next_fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">next_fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.next_fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id2">
-<span class="sig-name descname"><span class="pre">plot_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prediction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(16,</span> <span class="pre">9)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id2" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prediction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(16,</span> <span class="pre">9)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id2" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id3">
-<span class="sig-name descname"><span class="pre">plot_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prediction</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkslateblue'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkgreen'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_anomaly_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'slategray'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">12.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id3" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prediction</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkslateblue'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkgreen'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_anomaly_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'slategray'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">12.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id3" title="Link to this definition">¶</a></dt>
 <dd><p>Plot a forecast time series.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2395,17 +2403,17 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.plot_things">
-<span class="sig-name descname"><span class="pre">plot_things</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.plot_things" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_things</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.plot_things" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id4">
-<span class="sig-name descname"><span class="pre">plot_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vline</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#d4f74f',</span> <span class="pre">'#82ab5a',</span> <span class="pre">'#ff6c05',</span> <span class="pre">'#c12600']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id4" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vline</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#d4f74f',</span> <span class="pre">'#82ab5a',</span> <span class="pre">'#ff6c05',</span> <span class="pre">'#c12600']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id4" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id5">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_history</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_transformations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_organic</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id5" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_history</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_transformations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_organic</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id5" title="Link to this definition">¶</a></dt>
 <dd><p>Generate a forecast.</p>
 <p>future_regressor and regressor_per_series should only include new future values, history is already stored
 they should match on forecast_length and index of forecasts</p>
@@ -2425,18 +2433,18 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.predict_new_product">
-<span class="sig-name descname"><span class="pre">predict_new_product</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.predict_new_product" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_new_product</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.predict_new_product" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.process_components">
-<span class="sig-name descname"><span class="pre">process_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.process_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">process_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.process_components" title="Link to this definition">¶</a></dt>
 <dd><p>Scale and standardize component outputs.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id6">
-<span class="sig-name descname"><span class="pre">return_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id6" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">return_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id6" title="Link to this definition">¶</a></dt>
 <dd><p>Return additive elements of forecast, linear and trend. If impacts included, it is a multiplicative term.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2450,30 +2458,30 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.rolling_trend">
-<span class="sig-name descname"><span class="pre">rolling_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">trend_residuals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.rolling_trend" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">rolling_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">trend_residuals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.rolling_trend" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.scale_data">
-<span class="sig-name descname"><span class="pre">scale_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.scale_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">scale_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.scale_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.to_origin_space">
-<span class="sig-name descname"><span class="pre">to_origin_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.to_origin_space" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">to_origin_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.to_origin_space" title="Link to this definition">¶</a></dt>
 <dd><p>Take transformed outputs back to original feature space.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.Cassandra.treatment_causal_impact">
-<span class="sig-name descname"><span class="pre">treatment_causal_impact</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">intervention_dates</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.treatment_causal_impact" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">treatment_causal_impact</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">intervention_dates</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.Cassandra.treatment_causal_impact" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.EventRiskForecast">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">EventRiskForecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.95</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'UnivariateMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'distance_metric':</span> <span class="pre">'euclidean',</span> <span class="pre">'k':</span> <span class="pre">10,</span> <span class="pre">'pointed_method':</span> <span class="pre">'median',</span> <span class="pre">'return_result_windows':</span> <span class="pre">True,</span> <span class="pre">'window':</span> <span class="pre">14}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'fillna':</span> <span class="pre">'pchip',</span> <span class="pre">'transformation_params':</span> <span class="pre">{'0':</span> <span class="pre">{'method':</span> <span class="pre">0.5},</span> <span class="pre">'1':</span> <span class="pre">{},</span> <span class="pre">'2':</span> <span class="pre">{'fixed':</span> <span class="pre">False,</span> <span class="pre">'window':</span> <span class="pre">7},</span> <span class="pre">'3':</span> <span class="pre">{}},</span> <span class="pre">'transformations':</span> <span class="pre">{'0':</span> <span class="pre">'Slice',</span> <span class="pre">'1':</span> <span class="pre">'DifferencedTransformer',</span> <span class="pre">'2':</span> <span class="pre">'RollingMeanTransformer',</span> <span class="pre">'3':</span> <span class="pre">'MaxAbsScaler'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'max_generations':</span> <span class="pre">30,</span> <span class="pre">'n_jobs':</span> <span class="pre">'auto',</span> <span class="pre">'random_seed':</span> <span class="pre">321,</span> <span class="pre">'verbose':</span> <span class="pre">1}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">EventRiskForecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.95</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'UnivariateMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'distance_metric':</span> <span class="pre">'euclidean',</span> <span class="pre">'k':</span> <span class="pre">10,</span> <span class="pre">'pointed_method':</span> <span class="pre">'median',</span> <span class="pre">'return_result_windows':</span> <span class="pre">True,</span> <span class="pre">'window':</span> <span class="pre">14}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'fillna':</span> <span class="pre">'pchip',</span> <span class="pre">'transformation_params':</span> <span class="pre">{'0':</span> <span class="pre">{'method':</span> <span class="pre">0.5},</span> <span class="pre">'1':</span> <span class="pre">{},</span> <span class="pre">'2':</span> <span class="pre">{'fixed':</span> <span class="pre">False,</span> <span class="pre">'window':</span> <span class="pre">7},</span> <span class="pre">'3':</span> <span class="pre">{}},</span> <span class="pre">'transformations':</span> <span class="pre">{'0':</span> <span class="pre">'Slice',</span> <span class="pre">'1':</span> <span class="pre">'DifferencedTransformer',</span> <span class="pre">'2':</span> <span class="pre">'RollingMeanTransformer',</span> <span class="pre">'3':</span> <span class="pre">'MaxAbsScaler'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'max_generations':</span> <span class="pre">30,</span> <span class="pre">'n_jobs':</span> <span class="pre">'auto',</span> <span class="pre">'random_seed':</span> <span class="pre">321,</span> <span class="pre">'verbose':</span> <span class="pre">1}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Generate a risk score (0 to 1, but usually close to 0) for a future event exceeding user specified upper or lower bounds.</p>
 <p>Upper and lower limits can be one of four types, and may each be different.
@@ -2515,42 +2523,42 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.predict_historic">
-<span class="sig-name descname"><span class="pre">predict_historic</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.predict_historic" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_historic</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.predict_historic" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.generate_result_windows">
-<span class="sig-name descname"><span class="pre">generate_result_windows</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.generate_result_windows" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate_result_windows</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.generate_result_windows" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.generate_risk_array">
-<span class="sig-name descname"><span class="pre">generate_risk_array</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.generate_risk_array" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate_risk_array</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.generate_risk_array" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.generate_historic_risk_array">
-<span class="sig-name descname"><span class="pre">generate_historic_risk_array</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.generate_historic_risk_array" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate_historic_risk_array</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.generate_historic_risk_array" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.set_limit">
-<span class="sig-name descname"><span class="pre">set_limit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.set_limit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">set_limit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.set_limit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.plot">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.plot" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.plot" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
@@ -2565,7 +2573,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id9">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'event_risk'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['UnivariateMotif',</span> <span class="pre">'MultivariateMotif',</span> <span class="pre">'SectionalMotif',</span> <span class="pre">'ARCH',</span> <span class="pre">'MetricMotif',</span> <span class="pre">'SeasonalityMotif']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">autots_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id9" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'event_risk'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['UnivariateMotif',</span> <span class="pre">'MultivariateMotif',</span> <span class="pre">'SectionalMotif',</span> <span class="pre">'ARCH',</span> <span class="pre">'MetricMotif',</span> <span class="pre">'SeasonalityMotif']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">autots_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id9" title="Link to this definition">¶</a></dt>
 <dd><p>Shortcut for generating model params.</p>
 <p>args specified are those suggested for an otherwise normal AutoTS run</p>
 <dl class="field-list simple">
@@ -2584,13 +2592,13 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id10">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">generate_historic_risk_array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id10" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">generate_historic_risk_array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id10" title="Link to this definition">¶</a></dt>
 <dd><p>Given a df and a limit, returns a 0/1 array of whether limit was equaled or exceeded.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id11">
-<span class="sig-name descname"><span class="pre">generate_result_windows</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id11" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate_result_windows</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_forecast_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id11" title="Link to this definition">¶</a></dt>
 <dd><p>For event risk forecasting. Params default to class init but can be overridden here.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Returns<span class="colon">:</span></dt>
@@ -2604,13 +2612,13 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id12">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">generate_risk_array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_windows</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id12" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">generate_risk_array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result_windows</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id12" title="Link to this definition">¶</a></dt>
 <dd><p>Given a df and a limit, returns a 0/1 array of whether limit was equaled or exceeded.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id13">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">column_idx</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#838996',</span> <span class="pre">'#c0c0c0',</span> <span class="pre">'#dcdcdc',</span> <span class="pre">'#a9a9a9',</span> <span class="pre">'#808080',</span> <span class="pre">'#989898',</span> <span class="pre">'#808080',</span> <span class="pre">'#757575',</span> <span class="pre">'#696969',</span> <span class="pre">'#c9c0bb',</span> <span class="pre">'#c8c8c8',</span> <span class="pre">'#323232',</span> <span class="pre">'#e5e4e2',</span> <span class="pre">'#778899',</span> <span class="pre">'#4f666a',</span> <span class="pre">'#848482',</span> <span class="pre">'#414a4c',</span> <span class="pre">'#8a7f80',</span> <span class="pre">'#c4c3d0',</span> <span class="pre">'#bebebe',</span> <span class="pre">'#dbd7d2']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">up_low_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#ff4500',</span> <span class="pre">'#ff5349']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#6495ED'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_ylim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.0,</span> <span class="pre">0.5]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(14,</span> <span class="pre">8)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result_windows</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id13" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">column_idx</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#838996',</span> <span class="pre">'#c0c0c0',</span> <span class="pre">'#dcdcdc',</span> <span class="pre">'#a9a9a9',</span> <span class="pre">'#808080',</span> <span class="pre">'#989898',</span> <span class="pre">'#808080',</span> <span class="pre">'#757575',</span> <span class="pre">'#696969',</span> <span class="pre">'#c9c0bb',</span> <span class="pre">'#c8c8c8',</span> <span class="pre">'#323232',</span> <span class="pre">'#e5e4e2',</span> <span class="pre">'#778899',</span> <span class="pre">'#4f666a',</span> <span class="pre">'#848482',</span> <span class="pre">'#414a4c',</span> <span class="pre">'#8a7f80',</span> <span class="pre">'#c4c3d0',</span> <span class="pre">'#bebebe',</span> <span class="pre">'#dbd7d2']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">up_low_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#ff4500',</span> <span class="pre">'#ff5349']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#6495ED'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_ylim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.0,</span> <span class="pre">0.5]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(14,</span> <span class="pre">8)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result_windows</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id13" title="Link to this definition">¶</a></dt>
 <dd><p>Plot a sample of the risk forecast outcomes.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2628,7 +2636,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.EventRiskForecast.plot_eval">
-<span class="sig-name descname"><span class="pre">plot_eval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">column_idx</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#00BFFF']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">up_low_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#ff4500',</span> <span class="pre">'#ff5349']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#6495ED'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_ylim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.0,</span> <span class="pre">0.5]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(14,</span> <span class="pre">8)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.plot_eval" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_eval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">column_idx</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#00BFFF']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">up_low_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#ff4500',</span> <span class="pre">'#ff5349']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'#6495ED'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar_ylim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.0,</span> <span class="pre">0.5]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(14,</span> <span class="pre">8)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit_2d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_risk_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.EventRiskForecast.plot_eval" title="Link to this definition">¶</a></dt>
 <dd><p>Plot a sample of the risk forecast with known value vs risk score.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2647,13 +2655,13 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id14">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#id14" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#id14" title="Link to this definition">¶</a></dt>
 <dd><p>Returns forecast upper, lower risk probability arrays for input limits.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id15">
-<span class="sig-name descname"><span class="pre">predict_historic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id15" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_historic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id15" title="Link to this definition">¶</a></dt>
 <dd><p>Returns upper, lower risk probability arrays for input limits for the historic data.
 If manual numpy array limits are used, the limits will need to be appropriate shape (for df_train and eval_periods if used)</p>
 <dl class="field-list simple">
@@ -2669,7 +2677,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id16">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">set_limit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id16" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">set_limit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">direction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_periods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id16" title="Link to this definition">¶</a></dt>
 <dd><p>Handles all limit input styles and returns numpy array.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2690,7 +2698,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.GeneralTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">GeneralTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reconciliation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">GeneralTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reconciliation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Remove fillNA and then mathematical transformations.</p>
 <p>Expects a chronologically sorted pandas.DataFrame with a DatetimeIndex, only numeric data, and a ‘wide’ (one column per series) shape.</p>
@@ -2795,7 +2803,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.GeneralTransformer.fill_na">
-<span class="sig-name descname"><span class="pre">fill_na</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.fill_na" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fill_na</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.fill_na" title="Link to this definition">¶</a></dt>
 <dd><dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
@@ -2811,7 +2819,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.GeneralTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Apply transformations and return transformer object.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2822,18 +2830,18 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.GeneralTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Directly fit and apply transformations to convert df.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.GeneralTransformer.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.get_new_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.GeneralTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillzero</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillzero</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Undo the madness.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2849,7 +2857,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.GeneralTransformer.retrieve_transformer">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">retrieve_transformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.retrieve_transformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">retrieve_transformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.retrieve_transformer" title="Link to this definition">¶</a></dt>
 <dd><p>Retrieves a specific transformer object from a string.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2867,7 +2875,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.GeneralTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.GeneralTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Apply transformations to convert df.</p>
 </dd></dl>
 
@@ -2875,11 +2883,11 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.HolidayDetector">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">HolidayDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_occurrences</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">splash_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.65</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dayofmonth_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">HolidayDetector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_occurrences</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">splash_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.65</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dayofmonth_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.HolidayDetector.dates_to_holidays">
-<span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">style</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.dates_to_holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">style</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.dates_to_holidays" title="Link to this definition">¶</a></dt>
 <dd><p>Populate date information for a given pd.DatetimeIndex.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2900,48 +2908,48 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.HolidayDetector.detect">
-<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.detect" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.detect" title="Link to this definition">¶</a></dt>
 <dd><p>Run holiday detection. Input wide-style pandas time series.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.HolidayDetector.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.HolidayDetector.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.get_new_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.HolidayDetector.plot">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_anomalies</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.plot" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_anomalies</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot_kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.plot" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.HolidayDetector.plot_anomaly">
-<span class="sig-name descname"><span class="pre">plot_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.plot_anomaly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kwargs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.HolidayDetector.plot_anomaly" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.RandomTransform">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">RandomTransform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{None:</span> <span class="pre">0.0,</span> <span class="pre">'MinMaxScaler':</span> <span class="pre">0.03,</span> <span class="pre">'PowerTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'QuantileTransformer':</span> <span class="pre">0.03,</span> <span class="pre">'MaxAbsScaler':</span> <span class="pre">0.03,</span> <span class="pre">'StandardScaler':</span> <span class="pre">0.04,</span> <span class="pre">'RobustScaler':</span> <span class="pre">0.03,</span> <span class="pre">'PCA':</span> <span class="pre">0.01,</span> <span class="pre">'FastICA':</span> <span class="pre">0.01,</span> <span class="pre">'Detrend':</span> <span class="pre">0.02,</span> <span class="pre">'RollingMeanTransformer':</span> <span class="pre">0.02,</span> <span class="pre">'RollingMean100thN':</span> <span class="pre">0.01,</span> <span class="pre">'DifferencedTransformer':</span> <span class="pre">0.05,</span> <span class="pre">'SinTrend':</span> <span class="pre">0.01,</span> <span class="pre">'PctChangeTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'CumSumTransformer':</span> <span class="pre">0.02,</span> <span class="pre">'PositiveShift':</span> <span class="pre">0.02,</span> <span class="pre">'Log':</span> <span class="pre">0.01,</span> <span class="pre">'IntermittentOccurrence':</span> <span class="pre">0.01,</span> <span class="pre">'SeasonalDifference':</span> <span class="pre">0.06,</span> <span class="pre">'cffilter':</span> <span class="pre">0.01,</span> <span class="pre">'bkfilter':</span> <span class="pre">0.05,</span> <span class="pre">'convolution_filter':</span> <span class="pre">0.001,</span> <span class="pre">'HPFilter':</span> <span class="pre">0.01,</span> <span class="pre">'DatepartRegression':</span> <span class="pre">0.01,</span> <span class="pre">'ClipOutliers':</span> <span class="pre">0.03,</span> <span class="pre">'Discretize':</span> <span class="pre">0.01,</span> <span class="pre">'CenterLastValue':</span> <span class="pre">0.01,</span> <span class="pre">'Round':</span> <span class="pre">0.02,</span> <span class="pre">'Slice':</span> <span class="pre">0.02,</span> <span class="pre">'ScipyFilter':</span> <span class="pre">0.02,</span> <span class="pre">'STLFilter':</span> <span class="pre">0.01,</span> <span class="pre">'EWMAFilter':</span> <span class="pre">0.02,</span> <span class="pre">'MeanDifference':</span> <span class="pre">0.002,</span> <span class="pre">'BTCD':</span> <span class="pre">0.01,</span> <span class="pre">'Cointegration':</span> <span class="pre">0.01,</span> <span class="pre">'AlignLastValue':</span> <span class="pre">0.2,</span> <span class="pre">'AnomalyRemoval':</span> <span class="pre">0.03,</span> <span class="pre">'HolidayTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'LocalLinearTrend':</span> <span class="pre">0.01,</span> <span class="pre">'KalmanSmoothing':</span> <span class="pre">0.02,</span> <span class="pre">'RegressionFilter':</span> <span class="pre">0.02,</span> <span class="pre">'LevelShiftTransformer':</span> <span class="pre">0.03,</span> <span class="pre">'CenterSplit':</span> <span class="pre">0.01,</span> <span class="pre">'FFTFilter':</span> <span class="pre">0.01,</span> <span class="pre">'FFTDecomposition':</span> <span class="pre">0.01,</span> <span class="pre">'ReplaceConstant':</span> <span class="pre">0.02,</span> <span class="pre">'AlignLastDiff':</span> <span class="pre">0.01,</span> <span class="pre">'DiffSmoother':</span> <span class="pre">0.005,</span> <span class="pre">'HistoricValues':</span> <span class="pre">0.01,</span> <span class="pre">'BKBandpassFilter':</span> <span class="pre">0.01}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_prob_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'ffill':</span> <span class="pre">0.4,</span> <span class="pre">'fake_date':</span> <span class="pre">0.1,</span> <span class="pre">'rolling_mean':</span> <span class="pre">0.1,</span> <span class="pre">'rolling_mean_24':</span> <span class="pre">0.1,</span> <span class="pre">'IterativeImputer':</span> <span class="pre">0.025,</span> <span class="pre">'mean':</span> <span class="pre">0.06,</span> <span class="pre">'zero':</span> <span class="pre">0.05,</span> <span class="pre">'ffill_mean_biased':</span> <span class="pre">0.1,</span> <span class="pre">'median':</span> <span class="pre">0.03,</span> <span class="pre">None:</span> <span class="pre">0.001,</span> <span class="pre">'interpolate':</span> <span class="pre">0.4,</span> <span class="pre">'KNNImputer':</span> <span class="pre">0.05,</span> <span class="pre">'IterativeImputerExtraTrees':</span> <span class="pre">0.0001,</span> <span class="pre">'SeasonalityMotifImputer':</span> <span class="pre">0.1,</span> <span class="pre">'SeasonalityMotifImputerLinMix':</span> <span class="pre">0.01,</span> <span class="pre">'SeasonalityMotifImputer1K':</span> <span class="pre">0.01,</span> <span class="pre">'DatepartRegressionImputer':</span> <span class="pre">0.05}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fast_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">superfast_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">traditional_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_min_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_none</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_nan_fill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.RandomTransform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">RandomTransform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'AlignLastDiff':</span> <span class="pre">0.01,</span> <span class="pre">'AlignLastValue':</span> <span class="pre">0.2,</span> <span class="pre">'AnomalyRemoval':</span> <span class="pre">0.03,</span> <span class="pre">'BKBandpassFilter':</span> <span class="pre">0.01,</span> <span class="pre">'BTCD':</span> <span class="pre">0.01,</span> <span class="pre">'CenterLastValue':</span> <span class="pre">0.01,</span> <span class="pre">'CenterSplit':</span> <span class="pre">0.01,</span> <span class="pre">'ClipOutliers':</span> <span class="pre">0.03,</span> <span class="pre">'Cointegration':</span> <span class="pre">0.01,</span> <span class="pre">'CumSumTransformer':</span> <span class="pre">0.02,</span> <span class="pre">'DatepartRegression':</span> <span class="pre">0.01,</span> <span class="pre">'Detrend':</span> <span class="pre">0.02,</span> <span class="pre">'DiffSmoother':</span> <span class="pre">0.005,</span> <span class="pre">'DifferencedTransformer':</span> <span class="pre">0.05,</span> <span class="pre">'Discretize':</span> <span class="pre">0.01,</span> <span class="pre">'EWMAFilter':</span> <span class="pre">0.02,</span> <span class="pre">'FFTDecomposition':</span> <span class="pre">0.01,</span> <span class="pre">'FFTFilter':</span> <span class="pre">0.01,</span> <span class="pre">'FastICA':</span> <span class="pre">0.01,</span> <span class="pre">'HPFilter':</span> <span class="pre">0.01,</span> <span class="pre">'HistoricValues':</span> <span class="pre">0.01,</span> <span class="pre">'HolidayTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'IntermittentOccurrence':</span> <span class="pre">0.01,</span> <span class="pre">'KalmanSmoothing':</span> <span class="pre">0.02,</span> <span class="pre">'LevelShiftTransformer':</span> <span class="pre">0.03,</span> <span class="pre">'LocalLinearTrend':</span> <span class="pre">0.01,</span> <span class="pre">'Log':</span> <span class="pre">0.01,</span> <span class="pre">'MaxAbsScaler':</span> <span class="pre">0.03,</span> <span class="pre">'MeanDifference':</span> <span class="pre">0.002,</span> <span class="pre">'MinMaxScaler':</span> <span class="pre">0.03,</span> <span class="pre">'PCA':</span> <span class="pre">0.01,</span> <span class="pre">'PctChangeTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'PositiveShift':</span> <span class="pre">0.02,</span> <span class="pre">'PowerTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'QuantileTransformer':</span> <span class="pre">0.03,</span> <span class="pre">'RegressionFilter':</span> <span class="pre">0.02,</span> <span class="pre">'ReplaceConstant':</span> <span class="pre">0.02,</span> <span class="pre">'RobustScaler':</span> <span class="pre">0.03,</span> <span class="pre">'RollingMean100thN':</span> <span class="pre">0.01,</span> <span class="pre">'RollingMeanTransformer':</span> <span class="pre">0.02,</span> <span class="pre">'Round':</span> <span class="pre">0.02,</span> <span class="pre">'STLFilter':</span> <span class="pre">0.01,</span> <span class="pre">'ScipyFilter':</span> <span class="pre">0.02,</span> <span class="pre">'SeasonalDifference':</span> <span class="pre">0.06,</span> <span class="pre">'SinTrend':</span> <span class="pre">0.01,</span> <span class="pre">'Slice':</span> <span class="pre">0.02,</span> <span class="pre">'StandardScaler':</span> <span class="pre">0.04,</span> <span class="pre">'bkfilter':</span> <span class="pre">0.05,</span> <span class="pre">'cffilter':</span> <span class="pre">0.01,</span> <span class="pre">'convolution_filter':</span> <span class="pre">0.001,</span> <span class="pre">None:</span> <span class="pre">0.0}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_prob_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'DatepartRegressionImputer':</span> <span class="pre">0.05,</span> <span class="pre">'IterativeImputer':</span> <span class="pre">0.025,</span> <span class="pre">'IterativeImputerExtraTrees':</span> <span class="pre">0.0001,</span> <span class="pre">'KNNImputer':</span> <span class="pre">0.05,</span> <span class="pre">'SeasonalityMotifImputer':</span> <span class="pre">0.1,</span> <span class="pre">'SeasonalityMotifImputer1K':</span> <span class="pre">0.01,</span> <span class="pre">'SeasonalityMotifImputerLinMix':</span> <span class="pre">0.01,</span> <span class="pre">'fake_date':</span> <span class="pre">0.1,</span> <span class="pre">'ffill':</span> <span class="pre">0.4,</span> <span class="pre">'ffill_mean_biased':</span> <span class="pre">0.1,</span> <span class="pre">'interpolate':</span> <span class="pre">0.4,</span> <span class="pre">'mean':</span> <span class="pre">0.06,</span> <span class="pre">'median':</span> <span class="pre">0.03,</span> <span class="pre">'rolling_mean':</span> <span class="pre">0.1,</span> <span class="pre">'rolling_mean_24':</span> <span class="pre">0.1,</span> <span class="pre">'zero':</span> <span class="pre">0.05,</span> <span class="pre">None:</span> <span class="pre">0.001}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fast_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">superfast_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">traditional_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_min_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_none</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_nan_fill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.RandomTransform" title="Link to this definition">¶</a></dt>
 <dd><p>Return a dict of randomly choosen transformation selections.</p>
 <p>BTCD is used as a signal that slow parameters are allowed.</p>
 </dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.TransformTS">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">TransformTS</span></span><a class="headerlink" href="#autots.TransformTS" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">TransformTS</span></span><a class="headerlink" href="#autots.TransformTS" title="Link to this definition">¶</a></dt>
 <dd><p>alias of <a class="reference internal" href="autots.tools.html#autots.tools.transform.GeneralTransformer" title="autots.tools.transform.GeneralTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">GeneralTransformer</span></code></a></p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.create_lagged_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">create_lagged_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">summarize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">backfill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bfill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.create_lagged_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">create_lagged_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">summarize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">backfill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bfill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.create_lagged_regressor" title="Link to this definition">¶</a></dt>
 <dd><p>Create a regressor of features lagged by forecast length.
 Useful to some models that don’t otherwise use such information.</p>
 <p>It is recommended that the .head(forecast_length) of both regressor_train and the df for training are dropped.
@@ -2970,7 +2978,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.create_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">create_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['US']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple_binarized'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">summarize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">backfill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bfill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encode_holiday_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'anomaly_detector_params':</span> <span class="pre">{'forecast_params':</span> <span class="pre">None,</span> <span class="pre">'method':</span> <span class="pre">'mad',</span> <span class="pre">'method_params':</span> <span class="pre">{'alpha':</span> <span class="pre">0.05,</span> <span class="pre">'distribution':</span> <span class="pre">'gamma'},</span> <span class="pre">'transform_dict':</span> <span class="pre">{'fillna':</span> <span class="pre">None,</span> <span class="pre">'transformation_params':</span> <span class="pre">{'0':</span> <span class="pre">{}},</span> <span class="pre">'transformations':</span> <span class="pre">{'0':</span> <span class="pre">'DifferencedTransformer'}}},</span> <span class="pre">'output':</span> <span class="pre">'univariate',</span> <span class="pre">'splash_threshold':</span> <span class="pre">None,</span> <span class="pre">'threshold':</span> <span class="pre">0.8,</span> <span class="pre">'use_dayofmonth_holidays':</span> <span class="pre">True,</span> <span class="pre">'use_hebrew_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_islamic_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_lunar_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_lunar_weekday':</span> <span class="pre">False,</span> <span class="pre">'use_wkdeom_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_wkdom_holidays':</span> <span class="pre">True}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_regr_style</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preprocessing_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.create_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">create_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['US']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple_binarized'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">summarize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">backfill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bfill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encode_holiday_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'anomaly_detector_params':</span> <span class="pre">{'forecast_params':</span> <span class="pre">None,</span> <span class="pre">'method':</span> <span class="pre">'mad',</span> <span class="pre">'method_params':</span> <span class="pre">{'alpha':</span> <span class="pre">0.05,</span> <span class="pre">'distribution':</span> <span class="pre">'gamma'},</span> <span class="pre">'transform_dict':</span> <span class="pre">{'fillna':</span> <span class="pre">None,</span> <span class="pre">'transformation_params':</span> <span class="pre">{'0':</span> <span class="pre">{}},</span> <span class="pre">'transformations':</span> <span class="pre">{'0':</span> <span class="pre">'DifferencedTransformer'}}},</span> <span class="pre">'output':</span> <span class="pre">'univariate',</span> <span class="pre">'splash_threshold':</span> <span class="pre">None,</span> <span class="pre">'threshold':</span> <span class="pre">0.8,</span> <span class="pre">'use_dayofmonth_holidays':</span> <span class="pre">True,</span> <span class="pre">'use_hebrew_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_islamic_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_lunar_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_lunar_weekday':</span> <span class="pre">False,</span> <span class="pre">'use_wkdeom_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_wkdom_holidays':</span> <span class="pre">True}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_regr_style</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preprocessing_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.create_regressor" title="Link to this definition">¶</a></dt>
 <dd><p>Create a regressor from information available in the existing dataset.
 Components: are lagged data, datepart information, and holiday.</p>
 <p>This function has been confusing people. This is NOT necessary for machine learning models, in AutoTS they internally create more elaborate feature sets separately.
@@ -3012,7 +3020,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.infer_frequency">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">infer_frequency</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warn</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.infer_frequency" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">infer_frequency</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warn</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.infer_frequency" title="Link to this definition">¶</a></dt>
 <dd><p>Infer the frequency in a slightly more robust way.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3026,7 +3034,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_artificial">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_artificial</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_start</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_end</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_artificial" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_artificial</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_start</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_end</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_artificial" title="Link to this definition">¶</a></dt>
 <dd><p>Load artifically generated series from random distributions.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3041,7 +3049,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_daily">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_daily</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_daily" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_daily</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_daily" title="Link to this definition">¶</a></dt>
 <dd><p>Daily sample data.</p>
 <dl class="simple">
 <dt>wiki = [</dt><dd><p>“Germany”, “Thanksgiving”, ‘all’, ‘Microsoft’,
@@ -3064,13 +3072,13 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_hourly">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_hourly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_hourly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_hourly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_hourly" title="Link to this definition">¶</a></dt>
 <dd><p>Traffic data from the MN DOT via the UCI data repository.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_linear">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_linear</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_random</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_linear" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_linear</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_random</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_linear" title="Link to this definition">¶</a></dt>
 <dd><p>Create a dataset of just zeroes for testing edge case.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3088,7 +3096,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_live_daily">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_live_daily</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_start</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_end</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fred_key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fred_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['DGS10',</span> <span class="pre">'T5YIE',</span> <span class="pre">'SP500',</span> <span class="pre">'DCOILWTICO',</span> <span class="pre">'DEXUSEU',</span> <span class="pre">'WPU0911']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tickers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['MSFT']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trends_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['forecasting',</span> <span class="pre">'cycling',</span> <span class="pre">'microsoft']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trends_geo</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_data_types</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['AWND',</span> <span class="pre">'WSF2',</span> <span class="pre">'TAVG']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_stations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['USW00094846',</span> <span class="pre">'USW00014925']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_years</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_stations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['CT3',</span> <span class="pre">'SK8']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_species</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PM25'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_days</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">earthquake_days</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">earthquake_min_magnitude</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gsa_key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gov_domain_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['nasa.gov']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gov_domain_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">600</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wikipedia_pages</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Microsoft_Office',</span> <span class="pre">'List_of_highest-grossing_films']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wiki_language</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'en'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_event_types</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['%28Z%29+Winter+Weather',</span> <span class="pre">'%28Z%29+Winter+Storm']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">caiso_query</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ENE_SLRS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">timeout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">300.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sleep_seconds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_live_daily" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_live_daily</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_start</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_end</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fred_key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fred_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['DGS10',</span> <span class="pre">'T5YIE',</span> <span class="pre">'SP500',</span> <span class="pre">'DCOILWTICO',</span> <span class="pre">'DEXUSEU',</span> <span class="pre">'WPU0911']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tickers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['MSFT']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trends_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['forecasting',</span> <span class="pre">'cycling',</span> <span class="pre">'microsoft']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trends_geo</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_data_types</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['AWND',</span> <span class="pre">'WSF2',</span> <span class="pre">'TAVG']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_stations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['USW00094846',</span> <span class="pre">'USW00014925']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_years</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_stations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['CT3',</span> <span class="pre">'SK8']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_species</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PM25'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">london_air_days</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">earthquake_days</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">earthquake_min_magnitude</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gsa_key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gov_domain_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['nasa.gov']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gov_domain_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">600</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wikipedia_pages</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Microsoft_Office',</span> <span class="pre">'List_of_highest-grossing_films']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wiki_language</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'en'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weather_event_types</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['%28Z%29+Winter+Weather',</span> <span class="pre">'%28Z%29+Winter+Storm']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">caiso_query</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ENE_SLRS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">timeout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">300.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sleep_seconds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_live_daily" title="Link to this definition">¶</a></dt>
 <dd><p>Generates a dataframe of data up to the present day. Requires active internet connection.
 Try to be respectful of these free data sources by not calling too much too heavily.
 Pass None instead of specification lists to exclude a data source.</p>
@@ -3125,19 +3133,19 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_monthly">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_monthly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_monthly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_monthly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_monthly" title="Link to this definition">¶</a></dt>
 <dd><p>Federal Reserve of St. Louis monthly economic indicators.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_sine">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_sine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_random</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_sine" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_sine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'2021-01-01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">introduce_random</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">123</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_sine" title="Link to this definition">¶</a></dt>
 <dd><p>Create a dataset of just zeroes for testing edge case.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_weekdays">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_weekdays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_weekdays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_weekdays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_weekdays" title="Link to this definition">¶</a></dt>
 <dd><p>Test edge cases by creating a Series with values as day of week.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3153,19 +3161,19 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_weekly">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_weekly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_weekly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_weekly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_weekly" title="Link to this definition">¶</a></dt>
 <dd><p>Weekly petroleum industry data from the EIA.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.load_yearly">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_yearly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_yearly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">load_yearly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">long</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.load_yearly" title="Link to this definition">¶</a></dt>
 <dd><p>Federal Reserve of St. Louis annual economic indicators.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.long_to_wide">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">long_to_wide</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'datetime'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'series_id'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.long_to_wide" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">long_to_wide</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'datetime'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'series_id'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.long_to_wide" title="Link to this definition">¶</a></dt>
 <dd><p>Take long data and convert into wide, cleaner data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3193,7 +3201,7 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.model_forecast">
-<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">model_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">horizontal_subset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.model_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.</span></span><span class="sig-name descname"><span class="pre">model_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_param_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_transform_dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_negatives</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">startTimeStamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fail_on_forecast_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">template_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['Model',</span> <span class="pre">'ModelParameters',</span> <span class="pre">'TransformationParameters',</span> <span class="pre">'Ensemble']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">horizontal_subset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">current_model_file</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_gc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.model_forecast" title="Link to this definition">¶</a></dt>
 <dd><p>Takes numeric data, returns numeric forecasts.</p>
 <p>Only one model (albeit potentially an ensemble)!
 Horizontal ensembles can not be nested, other ensemble types can be.</p>
@@ -3325,21 +3333,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
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index 5ef2e021..7c2f283a 100644
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+++ b/docs/build/html/source/autots.models.html
@@ -1,17 +1,25 @@
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@@ -33,16 +41,16 @@
           <div class="body" role="main">
             
   <section id="autots-models-package">
-<h1>autots.models package<a class="headerlink" href="#autots-models-package" title="Permalink to this heading">¶</a></h1>
+<h1>autots.models package<a class="headerlink" href="#autots-models-package" title="Link to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading">¶</a></h2>
 </section>
 <section id="module-autots.models.arch">
-<span id="autots-models-arch-module"></span><h2>autots.models.arch module<a class="headerlink" href="#module-autots.models.arch" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-arch-module"></span><h2>autots.models.arch module<a class="headerlink" href="#module-autots.models.arch" title="Link to this heading">¶</a></h2>
 <p>Arch Models from arch package.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.arch.ARCH">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.arch.</span></span><span class="sig-name descname"><span class="pre">ARCH</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ARCH'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GARCH'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">o</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">power</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'normal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rescale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">simulations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_result_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.arch.</span></span><span class="sig-name descname"><span class="pre">ARCH</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ARCH'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GARCH'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">o</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">power</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'normal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rescale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">simulations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_result_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>ARCH model family from arch package. See arch package for arg details.
 Not to be confused with a linux distro.</p>
@@ -59,7 +67,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.arch.ARCH.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied .</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -70,19 +78,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.arch.ARCH.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.arch.ARCH.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.arch.ARCH.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.arch.ARCH.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -103,12 +111,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.models.base">
-<span id="autots-models-base-module"></span><h2>autots.models.base module<a class="headerlink" href="#module-autots.models.base" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-base-module"></span><h2>autots.models.base module<a class="headerlink" href="#module-autots.models.base" title="Link to this heading">¶</a></h2>
 <p>Base model information</p>
 <p>&#64;author: Colin</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.base.ModelObject">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">ModelObject</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Uninitiated</span> <span class="pre">Model</span> <span class="pre">Name'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fit_runtime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">datetime.timedelta(0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">ModelObject</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Uninitiated</span> <span class="pre">Model</span> <span class="pre">Name'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fit_runtime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">datetime.timedelta(0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Generic class for holding forecasting models.</p>
 <dl class="simple">
@@ -129,13 +137,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.ModelObject.basic_profile">
-<span class="sig-name descname"><span class="pre">basic_profile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.basic_profile" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">basic_profile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.basic_profile" title="Link to this definition">¶</a></dt>
 <dd><p>Capture basic training details.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.ModelObject.create_forecast_index">
-<span class="sig-name descname"><span class="pre">create_forecast_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.create_forecast_index" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">create_forecast_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.create_forecast_index" title="Link to this definition">¶</a></dt>
 <dd><p>Generate a pd.DatetimeIndex appropriate for a new forecast.</p>
 <div class="admonition warning">
 <p class="admonition-title">Warning</p>
@@ -145,93 +153,93 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.ModelObject.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.ModelObject.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.ModelObject.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.ModelObject.time">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">time</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.time" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">time</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.ModelObject.time" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">PredictionObject</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Uninitiated'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_index</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">predict_runtime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">datetime.timedelta(0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fit_runtime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">datetime.timedelta(0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_parameters</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_parameters</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_runtime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">datetime.timedelta(0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_metrics</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_timestamp</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">avg_metrics</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">avg_metrics_weighted</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_error</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">PredictionObject</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Uninitiated'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_index</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">predict_runtime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">datetime.timedelta(0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fit_runtime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">datetime.timedelta(0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_parameters</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_parameters</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_runtime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">datetime.timedelta(0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series_metrics</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_timestamp</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">avg_metrics</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">avg_metrics_weighted</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_error</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Generic class for holding forecast information.</p>
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.model_name">
-<span class="sig-name descname"><span class="pre">model_name</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.model_name" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">model_name</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.model_name" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.model_parameters">
-<span class="sig-name descname"><span class="pre">model_parameters</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.model_parameters" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">model_parameters</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.model_parameters" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.transformation_parameters">
-<span class="sig-name descname"><span class="pre">transformation_parameters</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.transformation_parameters" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transformation_parameters</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.transformation_parameters" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.forecast">
-<span class="sig-name descname"><span class="pre">forecast</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">forecast</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.forecast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.upper_forecast">
-<span class="sig-name descname"><span class="pre">upper_forecast</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.upper_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">upper_forecast</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.upper_forecast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.lower_forecast">
-<span class="sig-name descname"><span class="pre">lower_forecast</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.lower_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">lower_forecast</span></span><a class="headerlink" href="#autots.models.base.PredictionObject.lower_forecast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.long_form_results">
-<span class="sig-name descname"><span class="pre">long_form_results</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.long_form_results" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">long_form_results</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.long_form_results" title="Link to this definition">¶</a></dt>
 <dd><p>return complete results in long form</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.total_runtime">
-<span class="sig-name descname"><span class="pre">total_runtime</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.total_runtime" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">total_runtime</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.total_runtime" title="Link to this definition">¶</a></dt>
 <dd><p>return runtime for all model components in seconds</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.plot">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.plot" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.plot" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.evaluate">
-<span class="sig-name descname"><span class="pre">evaluate</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.evaluate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">evaluate</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.evaluate" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.apply_constraints">
-<span class="sig-name descname"><span class="pre">apply_constraints</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.apply_constraints" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">apply_constraints</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.apply_constraints" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id0">
-<span class="sig-name descname"><span class="pre">apply_constraints</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">constraint_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'quantile'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint_regularization</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_constraint</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_constraint</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id0" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">apply_constraints</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">constraint_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'quantile'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint_regularization</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_constraint</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_constraint</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id0" title="Link to this definition">¶</a></dt>
 <dd><p>Use constraint thresholds to adjust outputs by limit.
 Note that only one method of constraint can be used here, but if different methods are desired,
 this can be run twice, with None passed to the upper or lower constraint not being used.</p>
@@ -259,7 +267,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id1">
-<span class="sig-name descname"><span class="pre">evaluate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_weights</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_timestamp_errors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_error</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cumsum_A</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">diff_A</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id1" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">evaluate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">actual</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_weights</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_timestamp_errors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_error</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cumsum_A</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">diff_A</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_of_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id1" title="Link to this definition">¶</a></dt>
 <dd><p>Evalute prediction against test actual. Fills out attributes of base object.</p>
 <p>This fails with pd.NA values supplied.</p>
 <dl class="field-list simple">
@@ -290,13 +298,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.extract_ensemble_runtimes">
-<span class="sig-name descname"><span class="pre">extract_ensemble_runtimes</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.extract_ensemble_runtimes" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">extract_ensemble_runtimes</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.extract_ensemble_runtimes" title="Link to this definition">¶</a></dt>
 <dd><p>Return a dataframe of final runtimes per model for standard ensembles.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id2">
-<span class="sig-name descname"><span class="pre">long_form_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">id_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeriesID'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interval_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'PredictionInterval'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update_datetime_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datetime_column</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id2" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">long_form_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">id_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'SeriesID'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interval_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'PredictionInterval'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update_datetime_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datetime_column</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id2" title="Link to this definition">¶</a></dt>
 <dd><p>Export forecasts (including upper and lower) as single ‘long’ format output</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -316,7 +324,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id3">
-<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_zeroes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interpolate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">facecolor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'black'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper</span> <span class="pre">right'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title_substring</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vline</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id3" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_zeroes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interpolate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">facecolor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'black'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'upper</span> <span class="pre">right'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title_substring</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vline</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id3" title="Link to this definition">¶</a></dt>
 <dd><p>Generate an example plot of one series. Does not handle non-numeric forecasts.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -341,24 +349,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.plot_df">
-<span class="sig-name descname"><span class="pre">plot_df</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_zeroes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interpolate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.plot_df" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_df</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_zeroes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interpolate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.plot_df" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.plot_ensemble_runtimes">
-<span class="sig-name descname"><span class="pre">plot_ensemble_runtimes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">xlim_right</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.plot_ensemble_runtimes" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_ensemble_runtimes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">xlim_right</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.plot_ensemble_runtimes" title="Link to this definition">¶</a></dt>
 <dd><p>Plot ensemble runtimes by model type.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.base.PredictionObject.plot_grid">
-<span class="sig-name descname"><span class="pre">plot_grid</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interpolate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_zeroes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(24,</span> <span class="pre">18)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'AutoTS</span> <span class="pre">Forecasts'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.plot_grid" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_grid</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interpolate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_zeroes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(24,</span> <span class="pre">18)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'AutoTS</span> <span class="pre">Forecasts'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.PredictionObject.plot_grid" title="Link to this definition">¶</a></dt>
 <dd><p>Plots multiple series in a grid, if present. Mostly identical args to the single plot function.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id4">
-<span class="sig-name descname"><span class="pre">total_runtime</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#id4" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">total_runtime</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#id4" title="Link to this definition">¶</a></dt>
 <dd><p>Combine runtimes.</p>
 </dd></dl>
 
@@ -366,7 +374,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.base.apply_constraints">
-<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">apply_constraints</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint_regularization</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_constraint</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_constraint</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.apply_constraints" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">apply_constraints</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint_regularization</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_constraint</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_constraint</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.apply_constraints" title="Link to this definition">¶</a></dt>
 <dd><p>Use constraint thresholds to adjust outputs by limit.
 Note that only one method of constraint can be used here, but if different methods are desired,
 this can be run twice, with None passed to the upper or lower constraint not being used.</p>
@@ -398,41 +406,41 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.base.calculate_peak_density">
-<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">calculate_peak_density</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">group_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Model'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'TotalRuntimeSeconds'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.calculate_peak_density" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">calculate_peak_density</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">group_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Model'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'TotalRuntimeSeconds'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.calculate_peak_density" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.base.create_forecast_index">
-<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">create_forecast_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">frequency</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_last_date</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.create_forecast_index" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">create_forecast_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">frequency</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_last_date</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.create_forecast_index" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.base.create_seaborn_palette_from_cmap">
-<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">create_seaborn_palette_from_cmap</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cmap_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'gist_rainbow'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.create_seaborn_palette_from_cmap" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">create_seaborn_palette_from_cmap</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cmap_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'gist_rainbow'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.create_seaborn_palette_from_cmap" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.base.extract_single_series_from_horz">
-<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">extract_single_series_from_horz</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_parameters</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.extract_single_series_from_horz" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">extract_single_series_from_horz</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_parameters</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.extract_single_series_from_horz" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.base.extract_single_transformer">
-<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">extract_single_transformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_parameters</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_params</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.extract_single_transformer" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">extract_single_transformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_parameters</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_params</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.extract_single_transformer" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.base.plot_distributions">
-<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">plot_distributions</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">runtimes_data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">group_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Model'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'TotalRuntimeSeconds'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">xlim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">xlim_right</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title_suffix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.plot_distributions" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.base.</span></span><span class="sig-name descname"><span class="pre">plot_distributions</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">runtimes_data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">group_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Model'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_col</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'TotalRuntimeSeconds'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">xlim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">xlim_right</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title_suffix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.base.plot_distributions" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.models.basics">
-<span id="autots-models-basics-module"></span><h2>autots.models.basics module<a class="headerlink" href="#module-autots.models.basics" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-basics-module"></span><h2>autots.models.basics module<a class="headerlink" href="#module-autots.models.basics" title="Link to this heading">¶</a></h2>
 <p>Naives and Others Requiring No Additional Packages Beyond Numpy and Pandas</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.AverageValueNaive">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">AverageValueNaive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'AverageValueNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'median'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">AverageValueNaive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'AverageValueNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'median'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Naive forecasting predicting a dataframe of the series’ median values</p>
 <dl class="field-list simple">
@@ -446,7 +454,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.AverageValueNaive.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -457,19 +465,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.AverageValueNaive.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.AverageValueNaive.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.AverageValueNaive.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.AverageValueNaive.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -490,7 +498,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.BallTreeMultivariateMotif">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">BallTreeMultivariateMotif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'canberra'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sample_fraction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">BallTreeMultivariateMotif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'canberra'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sample_fraction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Forecasts using a nearest neighbors type model adapted for probabilistic time series.
 Many of these motifs will struggle when the forecast_length is large and history is short.</p>
@@ -511,7 +519,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.BallTreeMultivariateMotif.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -522,19 +530,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.BallTreeMultivariateMotif.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.BallTreeMultivariateMotif.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.BallTreeMultivariateMotif.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.BallTreeMultivariateMotif.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -555,7 +563,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.ConstantNaive">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">ConstantNaive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ConstantNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constant</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">ConstantNaive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ConstantNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constant</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Naive forecasting predicting a dataframe of zeroes (0’s)</p>
 <dl class="field-list simple">
@@ -570,7 +578,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.ConstantNaive.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -581,19 +589,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.ConstantNaive.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.ConstantNaive.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.ConstantNaive.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.ConstantNaive.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -614,11 +622,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.FFT">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">FFT</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'FFT'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2023</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_harmonics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detrend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">FFT</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'FFT'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2023</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_harmonics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detrend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.FFT.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -632,19 +640,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.FFT.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.FFT.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.FFT.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.FFT.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -665,7 +673,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.KalmanStateSpace">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">KalmanStateSpace</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'KalmanStateSpace'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state_transition</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[1,</span> <span class="pre">1],</span> <span class="pre">[0,</span> <span class="pre">1]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[0.1,</span> <span class="pre">0.0],</span> <span class="pre">[0.0,</span> <span class="pre">0.01]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[1,</span> <span class="pre">0]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">em_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'undefined'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">KalmanStateSpace</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'KalmanStateSpace'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state_transition</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[1,</span> <span class="pre">1],</span> <span class="pre">[0,</span> <span class="pre">1]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[0.1,</span> <span class="pre">0.0],</span> <span class="pre">[0.0,</span> <span class="pre">0.01]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[1,</span> <span class="pre">0]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">em_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'undefined'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Forecast using a state space model solved by a Kalman Filter.</p>
 <dl class="field-list simple">
@@ -679,12 +687,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.KalmanStateSpace.cost_function">
-<span class="sig-name descname"><span class="pre">cost_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">param</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.cost_function" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">cost_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">param</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.cost_function" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.KalmanStateSpace.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -695,24 +703,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.KalmanStateSpace.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.KalmanStateSpace.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.KalmanStateSpace.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.KalmanStateSpace.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -731,14 +739,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.KalmanStateSpace.tune_observational_noise">
-<span class="sig-name descname"><span class="pre">tune_observational_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.tune_observational_noise" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">tune_observational_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.KalmanStateSpace.tune_observational_noise" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.LastValueNaive">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">LastValueNaive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'LastValueNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">LastValueNaive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'LastValueNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Naive forecasting predicting a dataframe of the last series value</p>
 <dl class="field-list simple">
@@ -752,7 +760,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.LastValueNaive.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -763,19 +771,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.LastValueNaive.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.LastValueNaive.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.LastValueNaive.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.LastValueNaive.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -796,7 +804,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.MetricMotif">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">MetricMotif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MetricMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">comparison_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">combination_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mae'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">MetricMotif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MetricMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">comparison_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">combination_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mae'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Forecasts using a nearest neighbors type model adapted for probabilistic time series.
 This version is fully vectorized, using basic metrics for distance comparison.</p>
@@ -816,7 +824,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.MetricMotif.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -830,19 +838,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.MetricMotif.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.MetricMotif.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.MetricMotif.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MetricMotif.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -863,7 +871,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.Motif">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">Motif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Motif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'weighted_mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'minkowski'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_result_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">Motif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Motif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'weighted_mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'minkowski'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_result_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Forecasts using a nearest neighbors type model adapted for probabilistic time series.</p>
 <dl class="field-list simple">
@@ -887,7 +895,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.Motif.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -898,19 +906,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.Motif.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.Motif.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.Motif.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.Motif.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -931,7 +939,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.MotifSimulation">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">MotifSimulation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MotifSimulation'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phrase_len</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'5'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">comparison</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'magnitude_pct_change_sign'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shared</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'l2'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_motifs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">recency_weighting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cutoff_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cutoff_minimum</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'median'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">MotifSimulation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MotifSimulation'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phrase_len</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'5'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">comparison</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'magnitude_pct_change_sign'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shared</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'l2'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_motifs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">recency_weighting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cutoff_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cutoff_minimum</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'median'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>More dark magic created by the evil mastermind of this project.
 Basically a highly-customized KNN</p>
@@ -956,7 +964,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.MotifSimulation.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -967,19 +975,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.MotifSimulation.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.MotifSimulation.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.MotifSimulation.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.MotifSimulation.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1000,7 +1008,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.NVAR">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">NVAR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'NVAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ridge_param</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5e-06</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup_pts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed_pts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed_weighted</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'input_order'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">NVAR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'NVAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ridge_param</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5e-06</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup_pts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed_pts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed_weighted</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'input_order'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Nonlinear Variable Autoregression or ‘Next-Generation Reservoir Computing’</p>
 <p>based on <a class="reference external" href="https://github.com/quantinfo/ng-rc-paper-code/">https://github.com/quantinfo/ng-rc-paper-code/</a>
@@ -1023,7 +1031,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.NVAR.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1034,19 +1042,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.NVAR.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.NVAR.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.NVAR.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.NVAR.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1067,7 +1075,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalNaive">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">SeasonalNaive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'SeasonalNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lag_1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lag_2</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lastvalue'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">SeasonalNaive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'SeasonalNaive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lag_1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lag_2</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lastvalue'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Naive forecasting predicting a dataframe with seasonal (lag) forecasts.</p>
 <p>Concerto No. 2 in G minor, Op. 8, RV 315</p>
@@ -1085,7 +1093,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalNaive.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1096,19 +1104,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalNaive.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalNaive.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalNaive.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalNaive.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1129,7 +1137,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalityMotif">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">SeasonalityMotif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'SeasonalityMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mae'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'common_fourier'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">independent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">SeasonalityMotif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'SeasonalityMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mae'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'common_fourier'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">independent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Forecasts using a nearest neighbors type model adapted for probabilistic time series.
 This version is fully vectorized, using basic metrics for distance comparison.</p>
@@ -1150,7 +1158,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalityMotif.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1164,19 +1172,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalityMotif.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalityMotif.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SeasonalityMotif.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SeasonalityMotif.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1197,7 +1205,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.basics.SectionalMotif">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">SectionalMotif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'SectionalMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'weighted_mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'nan_euclidean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_differenced</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">SectionalMotif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'SectionalMotif'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'weighted_mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'nan_euclidean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_differenced</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Forecasts using a nearest neighbors type model adapted for probabilistic time series.
 This version takes the distance metric average for all series at once.</p>
@@ -1220,7 +1228,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SectionalMotif.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1234,19 +1242,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SectionalMotif.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SectionalMotif.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.basics.SectionalMotif.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.SectionalMotif.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1267,19 +1275,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.basics.ZeroesNaive">
-<span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">ZeroesNaive</span></span><a class="headerlink" href="#autots.models.basics.ZeroesNaive" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">ZeroesNaive</span></span><a class="headerlink" href="#autots.models.basics.ZeroesNaive" title="Link to this definition">¶</a></dt>
 <dd><p>alias of <a class="reference internal" href="#autots.models.basics.ConstantNaive" title="autots.models.basics.ConstantNaive"><code class="xref py py-class docutils literal notranslate"><span class="pre">ConstantNaive</span></code></a></p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.basics.looped_motif">
-<span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">looped_motif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">Xa</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Xb</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r_arr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'minkowski'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_result_windows</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.looped_motif" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">looped_motif</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">Xa</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Xb</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r_arr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'minkowski'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_result_windows</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.looped_motif" title="Link to this definition">¶</a></dt>
 <dd><p>inner function for Motif model.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.basics.predict_reservoir">
-<span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">predict_reservoir</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup_pts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ridge_param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2.5e-06</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed_pts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed_weighted</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.predict_reservoir" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.basics.</span></span><span class="sig-name descname"><span class="pre">predict_reservoir</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup_pts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ridge_param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2.5e-06</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed_pts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed_weighted</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.basics.predict_reservoir" title="Link to this definition">¶</a></dt>
 <dd><p>Nonlinear Variable Autoregression or ‘Next-Generation Reservoir Computing’</p>
 <p>based on <a class="reference external" href="https://github.com/quantinfo/ng-rc-paper-code/">https://github.com/quantinfo/ng-rc-paper-code/</a>
 Gauthier, D.J., Bollt, E., Griffith, A. et al. Next generation reservoir computing. Nat Commun 12, 5564 (2021).
@@ -1308,14 +1316,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.models.cassandra">
-<span id="autots-models-cassandra-module"></span><h2>autots.models.cassandra module<a class="headerlink" href="#module-autots.models.cassandra" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-cassandra-module"></span><h2>autots.models.cassandra module<a class="headerlink" href="#module-autots.models.cassandra" title="Link to this heading">¶</a></h2>
 <p>Cassandra Model.
 Created on Tue Sep 13 19:45:57 2022</p>
 <p>&#64;author: Colin
 with assistance from &#64;crgillespie22</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.cassandra.BayesianMultiOutputRegression">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">BayesianMultiOutputRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gaussian_prior_mean</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wishart_prior_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wishart_dof_excess</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.BayesianMultiOutputRegression" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">BayesianMultiOutputRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gaussian_prior_mean</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wishart_prior_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wishart_dof_excess</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.BayesianMultiOutputRegression" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Bayesian Linear Regression, conjugate prior update.</p>
 <dl class="field-list simple">
@@ -1330,24 +1338,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.BayesianMultiOutputRegression.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.BayesianMultiOutputRegression.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.BayesianMultiOutputRegression.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.BayesianMultiOutputRegression.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_std</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.BayesianMultiOutputRegression.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_std</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.BayesianMultiOutputRegression.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.BayesianMultiOutputRegression.sample_posterior">
-<span class="sig-name descname"><span class="pre">sample_posterior</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.BayesianMultiOutputRegression.sample_posterior" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">sample_posterior</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.BayesianMultiOutputRegression.sample_posterior" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">Cassandra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preprocessing_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaling</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BaseScaler'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts_intervention</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonalities</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['common_fourier']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_interaction_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_intervention</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate_feature</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressors_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">randomwalk_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_standin</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_anomaly_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'Model':</span> <span class="pre">'LastValueNaive',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_colinearity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.998</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_multicolinearity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">Cassandra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preprocessing_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaling</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BaseScaler'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts_intervention</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonalities</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['common_fourier']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_interaction_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_intervention</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate_feature</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multivariate_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressors_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">randomwalk_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_standin</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_anomaly_detector_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'Model':</span> <span class="pre">'LastValueNaive',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constraint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_colinearity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.998</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_multicolinearity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Explainable decomposition-based forecasting with advanced trend modeling and preprocessing.</p>
 <p>Tunc etiam fatis aperit Cassandra futuris
@@ -1381,68 +1389,68 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.holiday_detector.dates_to_holidays">
-<span class="sig-prename descclassname"><span class="pre">holiday_detector.</span></span><span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.holiday_detector.dates_to_holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">holiday_detector.</span></span><span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.holiday_detector.dates_to_holidays" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.create_forecast_index">
-<span class="sig-name descname"><span class="pre">create_forecast_index</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.create_forecast_index" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">create_forecast_index</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.create_forecast_index" title="Link to this definition">¶</a></dt>
 <dd><p>after .fit, can be used to create index of prediction</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.plot_forecast">
-<span class="sig-name descname"><span class="pre">plot_forecast</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.plot_forecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_forecast</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.plot_forecast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.plot_components">
-<span class="sig-name descname"><span class="pre">plot_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.plot_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.plot_components" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.plot_trend">
-<span class="sig-name descname"><span class="pre">plot_trend</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.plot_trend" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_trend</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.plot_trend" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.get_new_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.return_components">
-<span class="sig-name descname"><span class="pre">return_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.return_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">return_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.return_components" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..anomaly_detector.anomalies">
-<span class="sig-prename descclassname"><span class="pre">.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">anomalies</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..anomaly_detector.anomalies" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">anomalies</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..anomaly_detector.anomalies" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..anomaly_detector.scores">
-<span class="sig-prename descclassname"><span class="pre">.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">scores</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..anomaly_detector.scores" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.anomaly_detector.</span></span><span class="sig-name descname"><span class="pre">scores</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..anomaly_detector.scores" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..holiday_count">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">holiday_count</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..holiday_count" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">holiday_count</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..holiday_count" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..holidays">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">holidays</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">holidays</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..holidays" title="Link to this definition">¶</a></dt>
 <dd><dl class="field-list simple">
 <dt class="field-odd">Type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>series flags, holiday detector only</p>
@@ -1452,7 +1460,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..params">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">params</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">params</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
@@ -1462,94 +1470,94 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..x_array">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">x_array</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..x_array" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">x_array</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..x_array" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..predict_x_array">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">predict_x_array</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..predict_x_array" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">predict_x_array</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..predict_x_array" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..trend_train">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">trend_train</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..trend_train" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">trend_train</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..trend_train" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra..predicted_trend">
-<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">predicted_trend</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..predicted_trend" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">.</span></span><span class="sig-name descname"><span class="pre">predicted_trend</span></span><a class="headerlink" href="#autots.models.cassandra.Cassandra..predicted_trend" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.analyze_trend">
-<span class="sig-name descname"><span class="pre">analyze_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">slope</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">index</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.analyze_trend" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">analyze_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">slope</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">index</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.analyze_trend" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.auto_fit">
-<span class="sig-name descname"><span class="pre">auto_fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.auto_fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">auto_fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.auto_fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.base_scaler">
-<span class="sig-name descname"><span class="pre">base_scaler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.base_scaler" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">base_scaler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.base_scaler" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.compare_actual_components">
-<span class="sig-name descname"><span class="pre">compare_actual_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.compare_actual_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">compare_actual_components</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.compare_actual_components" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.create_t">
-<span class="sig-name descname"><span class="pre">create_t</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.create_t" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">create_t</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.create_t" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.cross_validate">
-<span class="sig-name descname"><span class="pre">cross_validate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.cross_validate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">cross_validate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.cross_validate" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.feature_importance">
-<span class="sig-name descname"><span class="pre">feature_importance</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.feature_importance" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">feature_importance</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.feature_importance" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id5">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical_groups</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id5" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical_groups</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id5" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_transformations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_history</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_transformations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_history</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id6">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id6" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id6" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.next_fit">
-<span class="sig-name descname"><span class="pre">next_fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.next_fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">next_fit</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.next_fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id7">
-<span class="sig-name descname"><span class="pre">plot_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prediction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(16,</span> <span class="pre">9)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id7" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prediction</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(16,</span> <span class="pre">9)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id7" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id8">
-<span class="sig-name descname"><span class="pre">plot_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prediction</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkslateblue'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkgreen'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_anomaly_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'slategray'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">12.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id8" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prediction</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkslateblue'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'darkgreen'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_anomaly_color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'slategray'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">12.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id8" title="Link to this definition">¶</a></dt>
 <dd><p>Plot a forecast time series.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1569,17 +1577,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.plot_things">
-<span class="sig-name descname"><span class="pre">plot_things</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.plot_things" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_things</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.plot_things" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id9">
-<span class="sig-name descname"><span class="pre">plot_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vline</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#d4f74f',</span> <span class="pre">'#82ab5a',</span> <span class="pre">'#ff6c05',</span> <span class="pre">'#c12600']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id9" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vline</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">colors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['#d4f74f',</span> <span class="pre">'#82ab5a',</span> <span class="pre">'#ff6c05',</span> <span class="pre">'#c12600']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_date</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id9" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id10">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_history</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_transformations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_organic</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id10" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_history</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flag_regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_model_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_forecast_transformations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_organic</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">past_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id10" title="Link to this definition">¶</a></dt>
 <dd><p>Generate a forecast.</p>
 <p>future_regressor and regressor_per_series should only include new future values, history is already stored
 they should match on forecast_length and index of forecasts</p>
@@ -1599,18 +1607,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.predict_new_product">
-<span class="sig-name descname"><span class="pre">predict_new_product</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.predict_new_product" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_new_product</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.predict_new_product" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.process_components">
-<span class="sig-name descname"><span class="pre">process_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.process_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">process_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.process_components" title="Link to this definition">¶</a></dt>
 <dd><p>Scale and standardize component outputs.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="id11">
-<span class="sig-name descname"><span class="pre">return_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id11" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">return_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">to_origin_space</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id11" title="Link to this definition">¶</a></dt>
 <dd><p>Return additive elements of forecast, linear and trend. If impacts included, it is a multiplicative term.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1624,85 +1632,85 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.rolling_trend">
-<span class="sig-name descname"><span class="pre">rolling_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">trend_residuals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.rolling_trend" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">rolling_trend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">trend_residuals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.rolling_trend" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.scale_data">
-<span class="sig-name descname"><span class="pre">scale_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.scale_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">scale_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.scale_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.to_origin_space">
-<span class="sig-name descname"><span class="pre">to_origin_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.to_origin_space" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">to_origin_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.to_origin_space" title="Link to this definition">¶</a></dt>
 <dd><p>Take transformed outputs back to original feature space.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.cassandra.Cassandra.treatment_causal_impact">
-<span class="sig-name descname"><span class="pre">treatment_causal_impact</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">intervention_dates</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.treatment_causal_impact" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">treatment_causal_impact</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">intervention_dates</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.Cassandra.treatment_causal_impact" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.clean_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">clean_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">in_d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'regr_'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.clean_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">clean_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">in_d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'regr_'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.clean_regressor" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.cost_function_dwae">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_dwae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_dwae" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_dwae</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_dwae" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.cost_function_l1">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_l1</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_l1" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_l1</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_l1" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.cost_function_l1_positive">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_l1_positive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_l1_positive" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_l1_positive</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_l1_positive" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.cost_function_l2">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_l2</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_l2" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_l2</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_l2" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.cost_function_quantile">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_quantile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_quantile" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">cost_function_quantile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.cost_function_quantile" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.create_t">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">create_t</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ds</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.create_t" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">create_t</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ds</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.create_t" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.fit_linear_model">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">fit_linear_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.fit_linear_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">fit_linear_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.fit_linear_model" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.lstsq_minimize">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">lstsq_minimize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">15000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cost_function</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'l1'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.lstsq_minimize" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">lstsq_minimize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">15000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cost_function</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'l1'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.lstsq_minimize" title="Link to this definition">¶</a></dt>
 <dd><p>Any cost function version of lin reg.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.cassandra.lstsq_solve">
-<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">lstsq_solve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lamb</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">identity_matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.lstsq_solve" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.cassandra.</span></span><span class="sig-name descname"><span class="pre">lstsq_solve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lamb</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">identity_matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.cassandra.lstsq_solve" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.models.dnn">
-<span id="autots-models-dnn-module"></span><h2>autots.models.dnn module<a class="headerlink" href="#module-autots.models.dnn" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-dnn-module"></span><h2>autots.models.dnn module<a class="headerlink" href="#module-autots.models.dnn" title="Link to this heading">¶</a></h2>
 <p>Neural Nets.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.dnn.KerasRNN">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.dnn.</span></span><span class="sig-name descname"><span class="pre">KerasRNN</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rnn_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'LSTM'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kernel_initializer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lecun_uniform'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_layer_sizes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(32,</span> <span class="pre">32,</span> <span class="pre">32)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">optimizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'adam'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'huber'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.KerasRNN" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.dnn.</span></span><span class="sig-name descname"><span class="pre">KerasRNN</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rnn_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'LSTM'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kernel_initializer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lecun_uniform'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_layer_sizes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(32,</span> <span class="pre">32,</span> <span class="pre">32)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">optimizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'adam'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'huber'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.KerasRNN" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Wrapper for Tensorflow Keras based RNN.</p>
 <dl class="field-list simple">
@@ -1722,13 +1730,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.dnn.KerasRNN.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.KerasRNN.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.KerasRNN.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train the model on dataframes of X and Y.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.dnn.KerasRNN.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.KerasRNN.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.KerasRNN.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Predict on dataframe of X.</p>
 </dd></dl>
 
@@ -1736,7 +1744,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.dnn.Transformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.dnn.</span></span><span class="sig-name descname"><span class="pre">Transformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">head_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_heads</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ff_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_transformer_blocks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mlp_units</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[128]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mlp_dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">optimizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'adam'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'huber'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.Transformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.dnn.</span></span><span class="sig-name descname"><span class="pre">Transformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">head_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_heads</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ff_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_transformer_blocks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mlp_units</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[128]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mlp_dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">optimizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'adam'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'huber'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.Transformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Wrapper for Tensorflow Keras based Transformer.</p>
 <p>based on: <a class="reference external" href="https://keras.io/examples/timeseries/timeseries_transformer_classification/">https://keras.io/examples/timeseries/timeseries_transformer_classification/</a></p>
@@ -1754,13 +1762,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.dnn.Transformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.Transformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.Transformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train the model on dataframes of X and Y.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.dnn.Transformer.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.Transformer.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.Transformer.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Predict on dataframe of X.</p>
 </dd></dl>
 
@@ -1768,21 +1776,21 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.dnn.transformer_build_model">
-<span class="sig-prename descclassname"><span class="pre">autots.models.dnn.</span></span><span class="sig-name descname"><span class="pre">transformer_build_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input_shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">head_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_heads</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ff_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_transformer_blocks</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mlp_units</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mlp_dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.transformer_build_model" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.dnn.</span></span><span class="sig-name descname"><span class="pre">transformer_build_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input_shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">head_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_heads</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ff_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_transformer_blocks</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mlp_units</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mlp_dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.transformer_build_model" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.dnn.transformer_encoder">
-<span class="sig-prename descclassname"><span class="pre">autots.models.dnn.</span></span><span class="sig-name descname"><span class="pre">transformer_encoder</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inputs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">head_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_heads</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ff_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.transformer_encoder" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.dnn.</span></span><span class="sig-name descname"><span class="pre">transformer_encoder</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inputs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">head_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_heads</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ff_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.dnn.transformer_encoder" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.models.ensemble">
-<span id="autots-models-ensemble-module"></span><h2>autots.models.ensemble module<a class="headerlink" href="#module-autots.models.ensemble" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-ensemble-module"></span><h2>autots.models.ensemble module<a class="headerlink" href="#module-autots.models.ensemble" title="Link to this heading">¶</a></h2>
 <p>Tools for generating and forecasting with ensembles of models.</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.BestNEnsemble">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">BestNEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.BestNEnsemble" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">BestNEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.BestNEnsemble" title="Link to this definition">¶</a></dt>
 <dd><p>Generate mean forecast for ensemble of models.</p>
 <p>model_weights and point_methods other than ‘mean’ are incompatible</p>
 <dl class="field-list simple">
@@ -1801,43 +1809,43 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.DistEnsemble">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">DistEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.DistEnsemble" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">DistEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.DistEnsemble" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast for distance ensemble.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.EnsembleForecast">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">EnsembleForecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prematched_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.EnsembleForecast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">EnsembleForecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prematched_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.EnsembleForecast" title="Link to this definition">¶</a></dt>
 <dd><p>Return PredictionObject for given ensemble method.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.EnsembleTemplateGenerator">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">EnsembleTemplateGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">initial_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">score_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_validation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.EnsembleTemplateGenerator" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">EnsembleTemplateGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">initial_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">score_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_validation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.EnsembleTemplateGenerator" title="Link to this definition">¶</a></dt>
 <dd><p>Generate class 1 (non-horizontal) ensemble templates given a table of results.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.HDistEnsemble">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">HDistEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.HDistEnsemble" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">HDistEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.HDistEnsemble" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast for per_series per distance ensembling.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.HorizontalEnsemble">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">HorizontalEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prematched_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.HorizontalEnsemble" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">HorizontalEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prematched_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.HorizontalEnsemble" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast for per_series ensembling.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.HorizontalTemplateGenerator">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">HorizontalTemplateGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">per_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'horizontal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset_flag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series2</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_specified</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.HorizontalTemplateGenerator" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">HorizontalTemplateGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">per_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ensemble</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'horizontal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset_flag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">per_series2</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_specified</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.HorizontalTemplateGenerator" title="Link to this definition">¶</a></dt>
 <dd><p>Generate horizontal ensemble templates given a table of results.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.MosaicEnsemble">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">MosaicEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prematched_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.MosaicEnsemble" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">MosaicEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecasts_runtime</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prematched_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.MosaicEnsemble" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast for mosaic ensembling.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1848,12 +1856,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.find_pattern">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">find_pattern</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">strings</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sep</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'-'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.find_pattern" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">find_pattern</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">strings</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sep</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'-'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.find_pattern" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.generalize_horizontal">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">generalize_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known_matches</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">available_models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.generalize_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">generalize_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known_matches</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">available_models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.generalize_horizontal" title="Link to this definition">¶</a></dt>
 <dd><p>generalize a horizontal model trained on a subset of all series</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1869,23 +1877,23 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.generate_crosshair_score">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">generate_crosshair_score</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">error_matrix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.generate_crosshair_score" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">generate_crosshair_score</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">error_matrix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.generate_crosshair_score" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.generate_crosshair_score_list">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">generate_crosshair_score_list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">error_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.generate_crosshair_score_list" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">generate_crosshair_score_list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">error_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.generate_crosshair_score_list" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.generate_mosaic_template">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">generate_mosaic_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">initial_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_ids</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">col_names</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_errors</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">smoothing_window</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'MAE'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_use</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.generate_mosaic_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">generate_mosaic_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">initial_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_ids</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">col_names</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_errors</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">smoothing_window</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'MAE'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_use</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.generate_mosaic_template" title="Link to this definition">¶</a></dt>
 <dd><p>Generate an ensemble template from results.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.horizontal_classifier">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">horizontal_classifier</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'whatever'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classifier_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.horizontal_classifier" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">horizontal_classifier</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'whatever'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classifier_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.horizontal_classifier" title="Link to this definition">¶</a></dt>
 <dd><p>CLassify unknown series with the appropriate model for horizontal ensembling.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1902,34 +1910,34 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.horizontal_xy">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">horizontal_xy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.horizontal_xy" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">horizontal_xy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.horizontal_xy" title="Link to this definition">¶</a></dt>
 <dd><p>Construct X, Y, X_predict features for generalization.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.is_horizontal">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">is_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.is_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">is_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.is_horizontal" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.is_mosaic">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">is_mosaic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.is_mosaic" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">is_mosaic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.is_mosaic" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.mlens_helper">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mlens_helper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">models</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'bestn'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mlens_helper" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mlens_helper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">models</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'bestn'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mlens_helper" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.mosaic_classifier">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mosaic_classifier</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classifier_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mosaic_classifier" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mosaic_classifier</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classifier_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mosaic_classifier" title="Link to this definition">¶</a></dt>
 <dd><p>CLassify unknown series with the appropriate model for mosaic ensembles.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.mosaic_or_horizontal">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mosaic_or_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">all_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mosaic_or_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mosaic_or_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">all_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mosaic_or_horizontal" title="Link to this definition">¶</a></dt>
 <dd><p>Take a mosaic or horizontal model and return series or models.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1940,7 +1948,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.mosaic_to_horizontal">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mosaic_to_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ModelParameters</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_period</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mosaic_to_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mosaic_to_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ModelParameters</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_period</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mosaic_to_horizontal" title="Link to this definition">¶</a></dt>
 <dd><p>Take a mosaic template and pull a single forecast step as a horizontal model.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1960,22 +1968,22 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.mosaic_xy">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mosaic_xy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mosaic_xy" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">mosaic_xy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">known</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.mosaic_xy" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.n_limited_horz">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">n_limited_horz</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">per_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">K</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">safety_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.n_limited_horz" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">n_limited_horz</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">per_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">K</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">safety_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.n_limited_horz" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.parse_forecast_length">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">parse_forecast_length</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.parse_forecast_length" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">parse_forecast_length</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.parse_forecast_length" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.parse_horizontal">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">parse_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">all_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_id</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_id</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.parse_horizontal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">parse_horizontal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">all_series</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_id</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_id</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.parse_horizontal" title="Link to this definition">¶</a></dt>
 <dd><p>Take a mosaic or horizontal model and return series or models.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1993,23 +2001,23 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.parse_mosaic">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">parse_mosaic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.parse_mosaic" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">parse_mosaic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ensemble</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.parse_mosaic" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.process_mosaic_arrays">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">process_mosaic_arrays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">local_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_ids</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_errors</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">total_vals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_use</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">smoothing_window</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.process_mosaic_arrays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">process_mosaic_arrays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">local_results</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_ids</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_mae_errors</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">total_vals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_to_use</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">smoothing_window</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.process_mosaic_arrays" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.ensemble.summarize_series">
-<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">summarize_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.summarize_series" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.ensemble.</span></span><span class="sig-name descname"><span class="pre">summarize_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.ensemble.summarize_series" title="Link to this definition">¶</a></dt>
 <dd><p>Summarize time series data. For now just df.describe().</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.models.gluonts">
-<span id="autots-models-gluonts-module"></span><h2>autots.models.gluonts module<a class="headerlink" href="#module-autots.models.gluonts" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-gluonts-module"></span><h2>autots.models.gluonts module<a class="headerlink" href="#module-autots.models.gluonts" title="Link to this heading">¶</a></h2>
 <p>GluonTS</p>
 <p>Best neuralnet models currently available, released by Amazon, scale well.
 Except it is really the only thing I use that runs mxnet, and it takes a while to train these guys…
@@ -2018,7 +2026,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 Stability is not the strong suit of GluonTS.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.gluonts.GluonTS">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.gluonts.</span></span><span class="sig-name descname"><span class="pre">GluonTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GluonTS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gluon_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DeepAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.gluonts.</span></span><span class="sig-name descname"><span class="pre">GluonTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GluonTS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gluon_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DeepAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>GluonTS based on mxnet.</p>
 <dl class="field-list simple">
@@ -2038,7 +2046,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.gluonts.GluonTS.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2049,24 +2057,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.gluonts.GluonTS.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.gluonts.GluonTS.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.gluonts.GluonTS.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.gluonts.GluonTS.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.gluonts.GluonTS.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2087,11 +2095,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.models.greykite">
-<span id="autots-models-greykite-module"></span><h2>autots.models.greykite module<a class="headerlink" href="#module-autots.models.greykite" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-greykite-module"></span><h2>autots.models.greykite module<a class="headerlink" href="#module-autots.models.greykite" title="Link to this heading">¶</a></h2>
 <p>Greykite.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.greykite.Greykite">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.greykite.</span></span><span class="sig-name descname"><span class="pre">Greykite</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Greykite'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">growth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.greykite.</span></span><span class="sig-name descname"><span class="pre">Greykite</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Greykite'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">growth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2106,7 +2114,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.greykite.Greykite.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2117,19 +2125,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.greykite.Greykite.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.greykite.Greykite.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.greykite.Greykite.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.Greykite.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2150,13 +2158,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.greykite.seek_the_oracle">
-<span class="sig-prename descclassname"><span class="pre">autots.models.greykite.</span></span><span class="sig-name descname"><span class="pre">seek_the_oracle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_index</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">col</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">freq</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'silverkite'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">growth</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'UnitedStates'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.seek_the_oracle" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.greykite.</span></span><span class="sig-name descname"><span class="pre">seek_the_oracle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_index</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">col</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">freq</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'silverkite'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">growth</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'UnitedStates'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.greykite.seek_the_oracle" title="Link to this definition">¶</a></dt>
 <dd><p>Internal. For loop or parallel version of Greykite.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.models.matrix_var">
-<span id="autots-models-matrix-var-module"></span><h2>autots.models.matrix_var module<a class="headerlink" href="#module-autots.models.matrix_var" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-matrix-var-module"></span><h2>autots.models.matrix_var module<a class="headerlink" href="#module-autots.models.matrix_var" title="Link to this heading">¶</a></h2>
 <p>VAR models based on matrix factorization and related methods.</p>
 <p>Heavily borrowing on the work of Xinyu Chen
 See <a class="reference external" href="https://github.com/xinychen/transdim">https://github.com/xinychen/transdim</a> and corresponding Medium articles</p>
@@ -2164,7 +2172,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 On entry to DLASCL parameter number  4 had an illegal value</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.matrix_var.LATC">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">LATC</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'LATC'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_horizon</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">[1]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">[0.33333333,</span> <span class="pre">0.33333333,</span> <span class="pre">0.33333333]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">LATC</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'LATC'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_horizon</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">[1]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">[0.33333333,</span> <span class="pre">0.33333333,</span> <span class="pre">0.33333333]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Low Rank Autoregressive Tensor Completion.
 Based on <a class="reference external" href="https://arxiv.org/abs/2104.14936">https://arxiv.org/abs/2104.14936</a>
@@ -2184,7 +2192,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.LATC.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied .</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2195,19 +2203,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.LATC.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.LATC.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.LATC.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.LATC.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2228,7 +2236,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.matrix_var.MAR">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">MAR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">family</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'gaussian'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">MAR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">family</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'gaussian'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Matrix Autoregressive model based on the code of Xinyu Chen.</p>
 <dl class="field-list simple">
@@ -2244,7 +2252,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.MAR.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied .</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2255,19 +2263,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.MAR.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.MAR.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.MAR.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.MAR.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2288,7 +2296,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.matrix_var.RRVAR">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">RRVAR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'RRVAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'als'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rank</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">RRVAR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'RRVAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'als'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rank</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Reduced Rank VAR models based on the code of Xinyu Chen.</p>
 <dl class="field-list simple">
@@ -2304,7 +2312,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.RRVAR.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied .</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2315,19 +2323,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.RRVAR.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.RRVAR.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.RRVAR.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.RRVAR.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2348,7 +2356,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.matrix_var.TMF">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">TMF</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'TMF'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rank</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">TMF</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'TMF'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rank</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Temporal Matrix Factorization VAR model based on the code of Xinyu Chen.</p>
 <dl class="field-list simple">
@@ -2364,7 +2372,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.TMF.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied .</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2375,19 +2383,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.TMF.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.TMF.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.matrix_var.TMF.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.TMF.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2408,108 +2416,108 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.conj_grad_w">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">conj_grad_w</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.conj_grad_w" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">conj_grad_w</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.conj_grad_w" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.conj_grad_x">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">conj_grad_x</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Psi</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.conj_grad_x" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">conj_grad_x</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Psi</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.conj_grad_x" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.dmd">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">dmd</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.dmd" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">dmd</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.dmd" title="Link to this definition">¶</a></dt>
 <dd><p>Dynamic Mode Decomposition (DMD) algorithm.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.dmd4cast">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">dmd4cast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_step</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.dmd4cast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">dmd4cast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_step</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.dmd4cast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.ell_w">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">ell_w</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.ell_w" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">ell_w</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.ell_w" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.ell_x">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">ell_x</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Psi</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.ell_x" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">ell_x</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Psi</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.ell_x" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.generate_Psi">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">generate_Psi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">T</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.generate_Psi" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">generate_Psi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">T</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.generate_Psi" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.latc_imputer">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">latc_imputer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_lags</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.latc_imputer" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">latc_imputer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_lags</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.latc_imputer" title="Link to this definition">¶</a></dt>
 <dd><p>Low-Rank Autoregressive Tensor Completion, LATC-imputer.
 Recognizes 0 as NaN.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.latc_predictor">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">latc_predictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_time_steps</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_horizon</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_intervals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_lags</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.latc_predictor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">latc_predictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_time_steps</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_horizon</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_intervals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_lags</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.latc_predictor" title="Link to this definition">¶</a></dt>
 <dd><p>LATC-predictor kernel.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.mar">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">mar</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_step</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">family</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'gaussian'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.mar" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">mar</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_step</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">family</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'gaussian'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.mar" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.mat2ten">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">mat2ten</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.mat2ten" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">mat2ten</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.mat2ten" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.rrvar">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">rrvar</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">R</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_step</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.rrvar" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">rrvar</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">R</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_step</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.rrvar" title="Link to this definition">¶</a></dt>
 <dd><p>Reduced-rank VAR algorithm using ALS.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.svt_tnn">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">svt_tnn</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tau</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.svt_tnn" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">svt_tnn</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tau</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.svt_tnn" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.ten2mat">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">ten2mat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.ten2mat" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">ten2mat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.ten2mat" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.tmf">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">tmf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rank</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.tmf" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">tmf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sparse_mat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rank</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rho</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_maxiter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.tmf" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.update_cg">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">update_cg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">var</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Aq</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rold</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.update_cg" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">update_cg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">var</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Aq</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rold</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.update_cg" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.var">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">var</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_step</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.var" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">var</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_step</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.var" title="Link to this definition">¶</a></dt>
 <dd><p>Simple VAR.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.matrix_var.var4cast">
-<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">var4cast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">delta</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.var4cast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.matrix_var.</span></span><span class="sig-name descname"><span class="pre">var4cast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">delta</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.matrix_var.var4cast" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.models.mlensemble">
-<span id="autots-models-mlensemble-module"></span><h2>autots.models.mlensemble module<a class="headerlink" href="#module-autots.models.mlensemble" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-mlensemble-module"></span><h2>autots.models.mlensemble module<a class="headerlink" href="#module-autots.models.mlensemble" title="Link to this heading">¶</a></h2>
 <p>Created on Sun Jan 15 19:28:57 2023</p>
 <p>&#64;author: Colin</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.mlensemble.MLEnsemble">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.mlensemble.</span></span><span class="sig-name descname"><span class="pre">MLEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MLEnsemble'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[{'Model':</span> <span class="pre">'Cassandra',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{},</span> <span class="pre">'TransformationParameters':</span> <span class="pre">{}},</span> <span class="pre">{'Model':</span> <span class="pre">'MetricMotif',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{},</span> <span class="pre">'TransformationParameters':</span> <span class="pre">{}},</span> <span class="pre">{'Model':</span> <span class="pre">'SeasonalityMotif',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{},</span> <span class="pre">'TransformationParameters':</span> <span class="pre">{}}]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'backwards'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'expanded_binarized'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.mlensemble.</span></span><span class="sig-name descname"><span class="pre">MLEnsemble</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MLEnsemble'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[{'Model':</span> <span class="pre">'Cassandra',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{},</span> <span class="pre">'TransformationParameters':</span> <span class="pre">{}},</span> <span class="pre">{'Model':</span> <span class="pre">'MetricMotif',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{},</span> <span class="pre">'TransformationParameters':</span> <span class="pre">{}},</span> <span class="pre">{'Model':</span> <span class="pre">'SeasonalityMotif',</span> <span class="pre">'ModelParameters':</span> <span class="pre">{},</span> <span class="pre">'TransformationParameters':</span> <span class="pre">{}}]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_validations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'backwards'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'expanded_binarized'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models_source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Combine models using an ML model across validations.</p>
 <dl class="field-list simple">
@@ -2523,7 +2531,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.mlensemble.MLEnsemble.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2537,19 +2545,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.mlensemble.MLEnsemble.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.mlensemble.MLEnsemble.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.mlensemble.MLEnsemble.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.MLEnsemble.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2570,31 +2578,31 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.mlensemble.create_feature">
-<span class="sig-prename descclassname"><span class="pre">autots.models.mlensemble.</span></span><span class="sig-name descname"><span class="pre">create_feature</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.create_feature" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.mlensemble.</span></span><span class="sig-name descname"><span class="pre">create_feature</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.mlensemble.create_feature" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.models.model_list">
-<span id="autots-models-model-list-module"></span><h2>autots.models.model_list module<a class="headerlink" href="#module-autots.models.model_list" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-model-list-module"></span><h2>autots.models.model_list module<a class="headerlink" href="#module-autots.models.model_list" title="Link to this heading">¶</a></h2>
 <p>Lists of models grouped by aspects.</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.model_list.auto_model_list">
-<span class="sig-prename descclassname"><span class="pre">autots.models.model_list.</span></span><span class="sig-name descname"><span class="pre">auto_model_list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.model_list.auto_model_list" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.model_list.</span></span><span class="sig-name descname"><span class="pre">auto_model_list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.model_list.auto_model_list" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.model_list.model_list_to_dict">
-<span class="sig-prename descclassname"><span class="pre">autots.models.model_list.</span></span><span class="sig-name descname"><span class="pre">model_list_to_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.model_list.model_list_to_dict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.model_list.</span></span><span class="sig-name descname"><span class="pre">model_list_to_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.model_list.model_list_to_dict" title="Link to this definition">¶</a></dt>
 <dd><p>Convert various possibilities to dict.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.models.neural_forecast">
-<span id="autots-models-neural-forecast-module"></span><h2>autots.models.neural_forecast module<a class="headerlink" href="#module-autots.models.neural_forecast" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-neural-forecast-module"></span><h2>autots.models.neural_forecast module<a class="headerlink" href="#module-autots.models.neural_forecast" title="Link to this heading">¶</a></h2>
 <p>Nixtla’s NeuralForecast. Be warned, as of writing, their package has commercial restrictions.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.neural_forecast.NeuralForecast">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.neural_forecast.</span></span><span class="sig-name descname"><span class="pre">NeuralForecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'NeuralForecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2023</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">28</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'LSTM'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'MQLoss'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'2ForecastLength'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_steps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">early_stop_patience_steps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">activation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'ReLU'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'robust'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_quantile</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.neural_forecast.</span></span><span class="sig-name descname"><span class="pre">NeuralForecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'NeuralForecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2023</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">28</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'LSTM'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'MQLoss'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'2ForecastLength'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_steps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">early_stop_patience_steps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">activation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'ReLU'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaler_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'robust'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">point_quantile</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>See NeuralForecast documentation for details.</p>
 <p>temp[‘ModelParameters’].str.extract(‘model”: “([a-zA-Z]+)’)</p>
@@ -2612,7 +2620,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.neural_forecast.NeuralForecast.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2623,31 +2631,31 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.neural_forecast.NeuralForecast.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.neural_forecast.NeuralForecast.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.neural_forecast.NeuralForecast.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.neural_forecast.NeuralForecast.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 </section>
 <section id="module-autots.models.prophet">
-<span id="autots-models-prophet-module"></span><h2>autots.models.prophet module<a class="headerlink" href="#module-autots.models.prophet" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-prophet-module"></span><h2>autots.models.prophet module<a class="headerlink" href="#module-autots.models.prophet" title="Link to this heading">¶</a></h2>
 <p>Facebook’s Prophet</p>
 <p>Since Prophet install can be finicky on Windows, it will be an optional dependency.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.prophet.FBProphet">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.prophet.</span></span><span class="sig-name descname"><span class="pre">FBProphet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'FBProphet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">yearly_seasonality</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weekly_seasonality</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">daily_seasonality</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">growth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_changepoints</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">changepoint_prior_scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'additive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">changepoint_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality_prior_scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holidays_prior_scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.prophet.</span></span><span class="sig-name descname"><span class="pre">FBProphet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'FBProphet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">yearly_seasonality</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weekly_seasonality</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">daily_seasonality</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">growth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_changepoints</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">changepoint_prior_scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'additive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">changepoint_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality_prior_scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holidays_prior_scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Facebook’s Prophet</p>
 <p>‘thou shall count to 3, no more, no less, 3 shall be the number thou shall count, and the number of the counting
@@ -2666,7 +2674,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.prophet.FBProphet.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2677,19 +2685,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.prophet.FBProphet.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.prophet.FBProphet.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.prophet.FBProphet.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.FBProphet.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2710,7 +2718,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.prophet.NeuralProphet">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.prophet.</span></span><span class="sig-name descname"><span class="pre">NeuralProphet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'NeuralProphet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">growth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'off'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_changepoints</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">changepoints_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_reg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_reg_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_sparsity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">yearly_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weekly_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">daily_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'additive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality_reg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_hidden_layers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d_hidden</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss_func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Huber'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_speed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.prophet.</span></span><span class="sig-name descname"><span class="pre">NeuralProphet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'NeuralProphet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">growth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'off'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_changepoints</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">changepoints_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_reg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend_reg_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_sparsity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">yearly_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weekly_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">daily_seasonality</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality_mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'additive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality_reg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_hidden_layers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d_hidden</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss_func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Huber'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_speed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Facebook’s Prophet got caught in a net.</p>
 <p>n_jobs is implemented here but it should be set to 1. PyTorch already maxes out cores in all observed cases.</p>
@@ -2727,7 +2735,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.prophet.NeuralProphet.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2738,19 +2746,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.prophet.NeuralProphet.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.prophet.NeuralProphet.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.prophet.NeuralProphet.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.prophet.NeuralProphet.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2771,12 +2779,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.models.pytorch">
-<span id="autots-models-pytorch-module"></span><h2>autots.models.pytorch module<a class="headerlink" href="#module-autots.models.pytorch" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-pytorch-module"></span><h2>autots.models.pytorch module<a class="headerlink" href="#module-autots.models.pytorch" title="Link to this heading">¶</a></h2>
 <p>Created on Tue May 24 13:32:12 2022</p>
 <p>&#64;author: Colin</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.pytorch.PytorchForecasting">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.pytorch.</span></span><span class="sig-name descname"><span class="pre">PytorchForecasting</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PytorchForecasting'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">90</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">128</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_encoder_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">12</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.03</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_layers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_target_scales</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_normalizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'EncoderNormalizer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'TemporalFusionTransformer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantiles</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">[0.01,</span> <span class="pre">0.1,</span> <span class="pre">0.22,</span> <span class="pre">0.36,</span> <span class="pre">0.5,</span> <span class="pre">0.64,</span> <span class="pre">0.78,</span> <span class="pre">0.9,</span> <span class="pre">0.99]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_kwargs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trainer_kwargs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">callbacks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.pytorch.</span></span><span class="sig-name descname"><span class="pre">PytorchForecasting</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PytorchForecasting'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">90</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">128</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_encoder_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">12</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.03</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_layers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_target_scales</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_normalizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'EncoderNormalizer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'TemporalFusionTransformer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantiles</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">[0.01,</span> <span class="pre">0.1,</span> <span class="pre">0.22,</span> <span class="pre">0.36,</span> <span class="pre">0.5,</span> <span class="pre">0.64,</span> <span class="pre">0.78,</span> <span class="pre">0.9,</span> <span class="pre">0.99]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_kwargs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trainer_kwargs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">callbacks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>pytorch-forecasting for the world’s over-obsession of neural nets.</p>
 <p>This is generally going to require more data than most other models.</p>
@@ -2795,7 +2803,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.pytorch.PytorchForecasting.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2806,19 +2814,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.pytorch.PytorchForecasting.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.pytorch.PytorchForecasting.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.pytorch.PytorchForecasting.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.pytorch.PytorchForecasting.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2840,12 +2848,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.models.sklearn">
-<span id="autots-models-sklearn-module"></span><h2>autots.models.sklearn module<a class="headerlink" href="#module-autots.models.sklearn" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-sklearn-module"></span><h2>autots.models.sklearn module<a class="headerlink" href="#module-autots.models.sklearn" title="Link to this heading">¶</a></h2>
 <p>Sklearn dependent models</p>
 <p>Decision Tree, Elastic Net,  Random Forest, MLPRegressor, KNN, Adaboost</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.sklearn.ComponentAnalysis">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">ComponentAnalysis</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ComponentAnalysis'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_components</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GLS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_parameters</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">decomposition</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PCA'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">ComponentAnalysis</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ComponentAnalysis'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_components</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GLS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_parameters</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">decomposition</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PCA'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Forecasting on principle components.</p>
 <dl class="field-list simple">
@@ -2863,7 +2871,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.ComponentAnalysis.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2874,19 +2882,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.ComponentAnalysis.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.ComponentAnalysis.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.ComponentAnalysis.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.ComponentAnalysis.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2907,7 +2915,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.sklearn.DatepartRegression">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">DatepartRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DatepartRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'DecisionTree',</span> <span class="pre">'model_params':</span> <span class="pre">{'max_depth':</span> <span class="pre">5,</span> <span class="pre">'min_samples_split':</span> <span class="pre">2}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'expanded'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">DatepartRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DatepartRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'DecisionTree',</span> <span class="pre">'model_params':</span> <span class="pre">{'max_depth':</span> <span class="pre">5,</span> <span class="pre">'min_samples_split':</span> <span class="pre">2}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'expanded'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Regression not on series but datetime</p>
 <dl class="field-list simple">
@@ -2921,7 +2929,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.DatepartRegression.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2932,24 +2940,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.DatepartRegression.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.DatepartRegression.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.DatepartRegression.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.DatepartRegression.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.DatepartRegression.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2970,7 +2978,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">MultivariateRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MultivariateRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile90_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile10_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nonzero_last_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">probabilistic</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale_full_X</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'learning_rate':</span> <span class="pre">0.1,</span> <span class="pre">'max_depth':</span> <span class="pre">20,</span> <span class="pre">'min_samples_leaf':</span> <span class="pre">4,</span> <span class="pre">'min_samples_split':</span> <span class="pre">5,</span> <span class="pre">'n_estimators':</span> <span class="pre">250}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration_lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_hash</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">MultivariateRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'MultivariateRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile90_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile10_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nonzero_last_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">probabilistic</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale_full_X</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'learning_rate':</span> <span class="pre">0.1,</span> <span class="pre">'max_depth':</span> <span class="pre">20,</span> <span class="pre">'min_samples_leaf':</span> <span class="pre">4,</span> <span class="pre">'min_samples_split':</span> <span class="pre">5,</span> <span class="pre">'n_estimators':</span> <span class="pre">250}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration_lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_hash</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Regression-framed approach to forecasting using sklearn.
 A multiariate version of rolling regression: ie each series is lagged independently but modeled together</p>
@@ -2987,12 +2995,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression.base_scaler">
-<span class="sig-name descname"><span class="pre">base_scaler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.base_scaler" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">base_scaler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.base_scaler" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3006,24 +3014,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3043,12 +3051,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression.scale_data">
-<span class="sig-name descname"><span class="pre">scale_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.scale_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">scale_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.scale_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.MultivariateRegression.to_origin_space">
-<span class="sig-name descname"><span class="pre">to_origin_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.to_origin_space" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">to_origin_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.MultivariateRegression.to_origin_space" title="Link to this definition">¶</a></dt>
 <dd><p>Take transformed outputs back to original feature space.</p>
 </dd></dl>
 
@@ -3056,7 +3064,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.sklearn.PreprocessingRegression">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">PreprocessingRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PreprocessingRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2023</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_history</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">one_step</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">processed_y</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'common_fourier'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">28</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">PreprocessingRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'PreprocessingRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2023</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_history</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">one_step</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">processed_y</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'common_fourier'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">28</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Regression use the last n values as the basis of training data.</p>
 <dl class="field-list simple">
@@ -3071,7 +3079,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.PreprocessingRegression.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3082,24 +3090,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.PreprocessingRegression.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.PreprocessingRegression.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.PreprocessingRegression.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.PreprocessingRegression.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.PreprocessingRegression.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3120,7 +3128,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.sklearn.RollingRegression">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">RollingRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'RollingRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'ExtraTrees',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile90_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile10_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nonzero_last_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_date_part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x_transform</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">RollingRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'RollingRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'ExtraTrees',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile90_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile10_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nonzero_last_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_date_part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x_transform</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>General regression-framed approach to forecasting using sklearn.</p>
 <p>Who are you who are so wise in the ways of science?
@@ -3138,7 +3146,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.RollingRegression.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3152,19 +3160,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.RollingRegression.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.RollingRegression.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.RollingRegression.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.RollingRegression.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3185,7 +3193,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.sklearn.UnivariateRegression">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">UnivariateRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'UnivariateRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'ExtraTrees',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_date_part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x_transform</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">UnivariateRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'UnivariateRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'ExtraTrees',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_date_part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x_transform</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Regression-framed approach to forecasting using sklearn.
 A univariate version of rolling regression: ie each series is modeled independently</p>
@@ -3204,7 +3212,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.UnivariateRegression.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3218,19 +3226,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.UnivariateRegression.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.UnivariateRegression.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.UnivariateRegression.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.UnivariateRegression.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3252,7 +3260,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.sklearn.VectorizedMultiOutputGPR">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">VectorizedMultiOutputGPR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'rbf'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda_prime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">7</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.VectorizedMultiOutputGPR" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">VectorizedMultiOutputGPR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'rbf'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lambda_prime</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">7</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.VectorizedMultiOutputGPR" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Gaussian Process Regressor.</p>
 <dl class="field-list simple">
@@ -3269,24 +3277,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.VectorizedMultiOutputGPR.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.VectorizedMultiOutputGPR.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.VectorizedMultiOutputGPR.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.VectorizedMultiOutputGPR.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.VectorizedMultiOutputGPR.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.VectorizedMultiOutputGPR.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.VectorizedMultiOutputGPR.predict_proba">
-<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.VectorizedMultiOutputGPR.predict_proba" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.VectorizedMultiOutputGPR.predict_proba" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.sklearn.WindowRegression">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">WindowRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'WindowRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'univariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast_length'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">WindowRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'WindowRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2022</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'univariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast_length'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Regression use the last n values as the basis of training data.</p>
 <dl class="field-list simple">
@@ -3301,7 +3309,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.WindowRegression.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3312,24 +3320,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.WindowRegression.fit_data">
-<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.fit_data" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.fit_data" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.WindowRegression.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.WindowRegression.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.sklearn.WindowRegression.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.WindowRegression.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3350,30 +3358,30 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.sklearn.generate_classifier_params">
-<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">generate_classifier_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'default'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.generate_classifier_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">generate_classifier_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'default'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.generate_classifier_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.sklearn.generate_regressor_params">
-<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">generate_regressor_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'default'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.generate_regressor_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">generate_regressor_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'default'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.generate_regressor_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new parameters for input to regressor.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.sklearn.retrieve_classifier">
-<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">retrieve_classifier</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{'bootstrap':</span> <span class="pre">False,</span> <span class="pre">'min_samples_leaf':</span> <span class="pre">1,</span> <span class="pre">'n_estimators':</span> <span class="pre">300}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose_bool</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multioutput</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.retrieve_classifier" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">retrieve_classifier</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{'bootstrap':</span> <span class="pre">False,</span> <span class="pre">'min_samples_leaf':</span> <span class="pre">1,</span> <span class="pre">'n_estimators':</span> <span class="pre">300}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose_bool</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multioutput</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.retrieve_classifier" title="Link to this definition">¶</a></dt>
 <dd><p>Convert a model param dict to model object for regression frameworks.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.sklearn.retrieve_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">retrieve_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{'bootstrap':</span> <span class="pre">False,</span> <span class="pre">'min_samples_leaf':</span> <span class="pre">1,</span> <span class="pre">'n_estimators':</span> <span class="pre">300}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose_bool</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multioutput</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.retrieve_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">retrieve_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'RandomForest',</span> <span class="pre">'model_params':</span> <span class="pre">{'bootstrap':</span> <span class="pre">False,</span> <span class="pre">'min_samples_leaf':</span> <span class="pre">1,</span> <span class="pre">'n_estimators':</span> <span class="pre">300}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose_bool</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multioutput</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.retrieve_regressor" title="Link to this definition">¶</a></dt>
 <dd><p>Convert a model param dict to model object for regression frameworks.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.sklearn.rolling_x_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">rolling_x_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile90_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile10_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nonzero_last_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_date_part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration_lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.rolling_x_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">rolling_x_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile90_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile10_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nonzero_last_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_date_part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration_lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.rolling_x_regressor" title="Link to this definition">¶</a></dt>
 <dd><p>Generate more features from initial time series.</p>
 <p>macd_periods ignored if mean_rolling is None.</p>
 <p>Returns a dataframe of statistical features. Will need to be shifted by 1 or more to match Y for forecast.
@@ -3383,20 +3391,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.sklearn.rolling_x_regressor_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">rolling_x_regressor_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile90_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile10_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nonzero_last_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_date_part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration_lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.rolling_x_regressor_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.sklearn.</span></span><span class="sig-name descname"><span class="pre">rolling_x_regressor_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macd_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile90_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile10_rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ewm_var_alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">additional_lag_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abs_energy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_autocorr_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nonzero_last_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">add_date_part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor_per_series</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">static_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cointegration_lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.sklearn.rolling_x_regressor_regressor" title="Link to this definition">¶</a></dt>
 <dd><p>Adds in the future_regressor.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.models.statsmodels">
-<span id="autots-models-statsmodels-module"></span><h2>autots.models.statsmodels module<a class="headerlink" href="#module-autots.models.statsmodels" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-statsmodels-module"></span><h2>autots.models.statsmodels module<a class="headerlink" href="#module-autots.models.statsmodels" title="Link to this heading">¶</a></h2>
 <p>Statsmodels based forecasting models.</p>
 <p>Statsmodels documentation can be a bit confusing.
 And it seems standard at first, but each model likes to do things differently.
 For example: exog, exog_oos, and exog_fc all sometimes mean the same thing</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARDL">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">ARDL</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ARDL'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">causal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'holiday'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">ARDL</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ARDL'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">causal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'holiday'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>ARDL from Statsmodels.</p>
 <dl class="field-list simple">
@@ -3415,7 +3423,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARDL.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied .</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3426,19 +3434,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARDL.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARDL.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARDL.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARDL.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3459,7 +3467,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARIMA">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">ARIMA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ARIMA'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">ARIMA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ARIMA'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>ARIMA from Statsmodels.</p>
 <dl class="field-list simple">
@@ -3478,7 +3486,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARIMA.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied .</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3489,20 +3497,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARIMA.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 <p>large p,d,q can be very slow (a p of 30 can take hours)</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARIMA.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ARIMA.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ARIMA.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3523,7 +3531,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactor">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">DynamicFactor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DynamicFactor'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_factors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">factor_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">DynamicFactor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DynamicFactor'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_factors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">factor_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>DynamicFactor from Statsmodels</p>
 <dl class="field-list simple">
@@ -3538,7 +3546,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactor.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3549,19 +3557,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactor.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactor.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactor.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactor.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3587,7 +3595,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactorMQ">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">DynamicFactorMQ</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DynamicFactorMQ'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">factors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">factor_orders</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">factor_multiplicities</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">idiosyncratic_ar1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">DynamicFactorMQ</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'DynamicFactorMQ'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">factors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">factor_orders</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">factor_multiplicities</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">idiosyncratic_ar1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>DynamicFactorMQ from Statsmodels</p>
 <dl class="field-list simple">
@@ -3601,7 +3609,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactorMQ.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3612,19 +3620,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactorMQ.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactorMQ.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.DynamicFactorMQ.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.DynamicFactorMQ.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3645,7 +3653,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ETS">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">ETS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ETS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">damped_trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonal_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">ETS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ETS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">damped_trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonal_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Exponential Smoothing from Statsmodels</p>
 <dl class="field-list simple">
@@ -3663,7 +3671,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ETS.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3674,19 +3682,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ETS.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ETS.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.ETS.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.ETS.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3707,7 +3715,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLM">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">GLM</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GLM'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">family</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Gaussian'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constant</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">GLM</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GLM'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">family</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'Gaussian'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constant</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Simple linear regression from statsmodels</p>
 <dl class="field-list simple">
@@ -3722,7 +3730,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLM.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3733,19 +3741,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLM.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLM.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLM.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLM.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3766,7 +3774,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLS">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">GLS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GLS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">GLS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GLS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Simple linear regression from statsmodels</p>
 <dl class="field-list simple">
@@ -3780,7 +3788,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLS.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3791,19 +3799,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLS.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Returns dict of new parameters for parameter tuning</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLS.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.GLS.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.GLS.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3824,7 +3832,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.Theta">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">Theta</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Theta'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deseasonalize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_test</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">difference</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">period</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_mle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">Theta</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Theta'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deseasonalize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_test</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">difference</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">period</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_mle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Theta Model from Statsmodels</p>
 <dl class="field-list simple">
@@ -3839,7 +3847,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.Theta.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3850,19 +3858,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.Theta.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.Theta.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.Theta.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.Theta.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3883,7 +3891,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.UnobservedComponents">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">UnobservedComponents</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'UnobservedComponents'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">level</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'smooth</span> <span class="pre">trend'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cycle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">damped_cycle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">irregular</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">autoregressive</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stochastic_cycle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stochastic_trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stochastic_level</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cov_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'opg'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lbfgs'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_kwargs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">UnobservedComponents</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'UnobservedComponents'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">level</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'smooth</span> <span class="pre">trend'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cycle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">damped_cycle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">irregular</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">autoregressive</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stochastic_cycle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stochastic_trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stochastic_level</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cov_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'opg'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lbfgs'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_kwargs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>UnobservedComponents from Statsmodels.</p>
 <dl class="field-list simple">
@@ -3899,7 +3907,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.UnobservedComponents.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3910,19 +3918,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.UnobservedComponents.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.UnobservedComponents.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.UnobservedComponents.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.UnobservedComponents.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3943,7 +3951,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VAR">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">VAR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'VAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxlags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">15</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ic</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'fpe'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">VAR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'VAR'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxlags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">15</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ic</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'fpe'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>VAR from Statsmodels.</p>
 <dl class="field-list simple">
@@ -3958,7 +3966,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VAR.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3969,19 +3977,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VAR.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VAR.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VAR.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VAR.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4002,7 +4010,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VARMAX">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">VARMAX</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'VARMAX'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(1,</span> <span class="pre">0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">VARMAX</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'VARMAX'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(1,</span> <span class="pre">0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>VARMAX from Statsmodels</p>
 <dl class="field-list simple">
@@ -4017,7 +4025,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VARMAX.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4028,19 +4036,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VARMAX.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VARMAX.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VARMAX.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VARMAX.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generate forecast data immediately following dates of index supplied to .fit().</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4061,7 +4069,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VECM">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">VECM</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'VECM'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deterministic</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'n'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_ar_diff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasons</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">coint_rank</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">VECM</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'VECM'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deterministic</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'n'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_ar_diff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasons</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">coint_rank</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>VECM from Statsmodels</p>
 <dl class="field-list simple">
@@ -4076,7 +4084,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VECM.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4087,19 +4095,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VECM.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VECM.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.statsmodels.VECM.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.VECM.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4120,21 +4128,21 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.statsmodels.arima_seek_the_oracle">
-<span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">arima_seek_the_oracle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">current_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.arima_seek_the_oracle" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">arima_seek_the_oracle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">current_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.arima_seek_the_oracle" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.statsmodels.glm_forecast_by_column">
-<span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">glm_forecast_by_column</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">current_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Xf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.glm_forecast_by_column" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.statsmodels.</span></span><span class="sig-name descname"><span class="pre">glm_forecast_by_column</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">current_series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Xf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.statsmodels.glm_forecast_by_column" title="Link to this definition">¶</a></dt>
 <dd><p>Run one series of GLM and return prediction.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.models.tfp">
-<span id="autots-models-tfp-module"></span><h2>autots.models.tfp module<a class="headerlink" href="#module-autots.models.tfp" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-tfp-module"></span><h2>autots.models.tfp module<a class="headerlink" href="#module-autots.models.tfp" title="Link to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.tfp.TFPRegression">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tfp.</span></span><span class="sig-name descname"><span class="pre">TFPRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'TFPRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kernel_initializer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lecun_uniform'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">optimizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'adam'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'negloglike'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'normal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tfp.</span></span><span class="sig-name descname"><span class="pre">TFPRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'TFPRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kernel_initializer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lecun_uniform'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">optimizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'adam'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'negloglike'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'normal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Tensorflow Probability regression.</p>
 <dl class="field-list simple">
@@ -4149,7 +4157,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TFPRegression.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4160,19 +4168,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TFPRegression.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TFPRegression.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TFPRegression.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegression.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4193,7 +4201,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.tfp.TFPRegressor">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tfp.</span></span><span class="sig-name descname"><span class="pre">TFPRegressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel_initializer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lecun_uniform'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">optimizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'adam'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'negloglike'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'normal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegressor" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tfp.</span></span><span class="sig-name descname"><span class="pre">TFPRegressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel_initializer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lecun_uniform'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">optimizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'adam'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'negloglike'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'normal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegressor" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Wrapper for Tensorflow Keras based RNN.</p>
 <dl class="field-list simple">
@@ -4213,13 +4221,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TFPRegressor.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegressor.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegressor.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train the model on dataframes of X and Y.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TFPRegressor.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">conf_int</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegressor.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">conf_int</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TFPRegressor.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Predict on dataframe of X.</p>
 </dd></dl>
 
@@ -4227,7 +4235,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.tfp.TensorflowSTS">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tfp.</span></span><span class="sig-name descname"><span class="pre">TensorflowSTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'TensorflowSTS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'local'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonal_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fit_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hmc'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tfp.</span></span><span class="sig-name descname"><span class="pre">TensorflowSTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'TensorflowSTS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'local'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonal_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fit_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hmc'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>STS from TensorflowProbability.</p>
 <dl class="field-list simple">
@@ -4242,7 +4250,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TensorflowSTS.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Train algorithm given data supplied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4253,19 +4261,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TensorflowSTS.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TensorflowSTS.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tfp.TensorflowSTS.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tfp.TensorflowSTS.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Generates forecast data immediately following dates of index supplied to .fit()</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4286,45 +4294,45 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.models.tide">
-<span id="autots-models-tide-module"></span><h2>autots.models.tide module<a class="headerlink" href="#module-autots.models.tide" title="Permalink to this heading">¶</a></h2>
+<span id="autots-models-tide-module"></span><h2>autots.models.tide module<a class="headerlink" href="#module-autots.models.tide" title="Link to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.tide.TiDE">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">TiDE</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'UnivariateRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">42</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'D'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0009999</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer_norm</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">512</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_layers</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hist_len</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">720</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">decoder_output_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">final_decoder_hidden</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_num_epochs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_epochs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">patience</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch_len</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">permute</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gpu_index</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">TiDE</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'UnivariateRegression'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">42</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'D'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0009999</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer_norm</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">512</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_layers</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hist_len</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">720</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">decoder_output_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">final_decoder_hidden</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_num_epochs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_epochs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">patience</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch_len</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">permute</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gpu_index</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">14</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.models.base.ModelObject" title="autots.models.base.ModelObject"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelObject</span></code></a></p>
 <p>Google Research MLP based forecasting approach.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tide.TiDE.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_cov_cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cat_cov_cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_cov_cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cat_cov_cols</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Training TS code.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tide.TiDE.get_new_params">
-<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE.get_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of new parameters for parameter tuning.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tide.TiDE.get_params">
-<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE.get_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE.get_params" title="Link to this definition">¶</a></dt>
 <dd><p>Return dict of current parameters.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tide.TiDE.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'test'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'self'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'test'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">just_point_forecast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TiDE.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.tide.TimeCovariates">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">TimeCovariates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetimes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalized</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeCovariates" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">TimeCovariates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetimes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalized</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeCovariates" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Extract all time covariates except for holidays.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tide.TimeCovariates.get_covariates">
-<span class="sig-name descname"><span class="pre">get_covariates</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeCovariates.get_covariates" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get_covariates</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeCovariates.get_covariates" title="Link to this definition">¶</a></dt>
 <dd><p>Get all time covariates.</p>
 </dd></dl>
 
@@ -4332,24 +4340,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.models.tide.TimeSeriesdata">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">TimeSeriesdata</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_cov_cols</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cat_cov_cols</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ts_cols</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_range</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_range</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_range</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hist_len</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_len</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">freq</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'D'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch_len</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">permute</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeSeriesdata" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">TimeSeriesdata</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_cov_cols</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cat_cov_cols</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ts_cols</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_range</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_range</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_range</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hist_len</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_len</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">freq</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'D'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch_len</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">permute</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeSeriesdata" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Data loader class.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tide.TimeSeriesdata.test_val_gen">
-<span class="sig-name descname"><span class="pre">test_val_gen</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'val'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeSeriesdata.test_val_gen" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">test_val_gen</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'val'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeSeriesdata.test_val_gen" title="Link to this definition">¶</a></dt>
 <dd><p>Generator for validation/test data.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tide.TimeSeriesdata.tf_dataset">
-<span class="sig-name descname"><span class="pre">tf_dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'train'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeSeriesdata.tf_dataset" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">tf_dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'train'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeSeriesdata.tf_dataset" title="Link to this definition">¶</a></dt>
 <dd><p>Tensorflow Dataset.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.models.tide.TimeSeriesdata.train_gen">
-<span class="sig-name descname"><span class="pre">train_gen</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeSeriesdata.train_gen" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">train_gen</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.TimeSeriesdata.train_gen" title="Link to this definition">¶</a></dt>
 <dd><p>Generator for training data.</p>
 </dd></dl>
 
@@ -4357,42 +4365,42 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.tide.get_HOLIDAYS">
-<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">get_HOLIDAYS</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.get_HOLIDAYS" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">get_HOLIDAYS</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.get_HOLIDAYS" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.tide.mae_loss">
-<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">mae_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.mae_loss" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">mae_loss</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.mae_loss" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.tide.mape">
-<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">mape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.mape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">mape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.mape" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.tide.nrmse">
-<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">nrmse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.nrmse" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">nrmse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.nrmse" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.tide.rmse">
-<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">rmse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.rmse" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">rmse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.rmse" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.tide.smape">
-<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">smape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.smape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">smape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.smape" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.models.tide.wape">
-<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">wape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.wape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.models.tide.</span></span><span class="sig-name descname"><span class="pre">wape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.models.tide.wape" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.models">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.models" title="Permalink to this heading">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.models" title="Link to this heading">¶</a></h2>
 <p>Model Models</p>
 </section>
 </section>
@@ -4487,21 +4495,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/source/autots.templates.html b/docs/build/html/source/autots.templates.html
index 283069f1..33235878 100644
--- a/docs/build/html/source/autots.templates.html
+++ b/docs/build/html/source/autots.templates.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="../">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>autots.templates package &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
-    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/doctools.js"></script>
-    <script src="../_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css?v=a4fa0645" />
+    <script src="../_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="../_static/doctools.js?v=888ff710"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
     <link rel="next" title="autots.tools package" href="autots.tools.html" />
@@ -33,16 +41,16 @@
           <div class="body" role="main">
             
   <section id="autots-templates-package">
-<h1>autots.templates package<a class="headerlink" href="#autots-templates-package" title="Permalink to this heading">¶</a></h1>
+<h1>autots.templates package<a class="headerlink" href="#autots-templates-package" title="Link to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading">¶</a></h2>
 </section>
 <section id="module-autots.templates.general">
-<span id="autots-templates-general-module"></span><h2>autots.templates.general module<a class="headerlink" href="#module-autots.templates.general" title="Permalink to this heading">¶</a></h2>
+<span id="autots-templates-general-module"></span><h2>autots.templates.general module<a class="headerlink" href="#module-autots.templates.general" title="Link to this heading">¶</a></h2>
 <p>Starting templates for models.</p>
 <dl class="py data">
 <dt class="sig sig-object py" id="autots.templates.general.general_template">
-<span class="sig-prename descclassname"><span class="pre">autots.templates.general.</span></span><span class="sig-name descname"><span class="pre">general_template</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">Model</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">ModelParameters</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">TransformationParameters</span>&#160; <span class="pre">Ensemble</span> <span class="pre">1</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">ARIMA</span>&#160; <span class="pre">{&quot;p&quot;:</span> <span class="pre">4,</span> <span class="pre">&quot;d&quot;:</span> <span class="pre">0,</span> <span class="pre">&quot;q&quot;:</span> <span class="pre">12,</span> <span class="pre">&quot;regression_type&quot;:</span> <span class="pre">n...</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;cubic&quot;,</span> <span class="pre">&quot;transformations&quot;:</span> <span class="pre">{&quot;0&quot;:</span> <span class="pre">&quot;...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">3</span>&#160;&#160;&#160; <span class="pre">AverageValueNaive</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">{&quot;method&quot;:</span> <span class="pre">&quot;Mean&quot;}</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;fake_date&quot;,</span> <span class="pre">&quot;transformations&quot;:</span> <span class="pre">{&quot;0...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">4</span>&#160;&#160;&#160; <span class="pre">AverageValueNaive</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">{&quot;method&quot;:</span> <span class="pre">&quot;Mean&quot;}</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;mean&quot;,</span> <span class="pre">&quot;transformations&quot;:</span> <span class="pre">{&quot;0&quot;:</span> <span class="pre">&quot;C...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">5</span>&#160;&#160;&#160; <span class="pre">AverageValueNaive</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">{&quot;method&quot;:</span> <span class="pre">&quot;Mean&quot;}</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;rolling_mean_24&quot;,</span> <span class="pre">&quot;transformations...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">6</span>&#160;&#160; <span class="pre">DatepartRegression</span>&#160; <span class="pre">{&quot;regression_model&quot;:</span> <span class="pre">{&quot;model&quot;:</span> <span class="pre">&quot;DecisionTree&quot;,...</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;mean&quot;,</span> <span class="pre">&quot;transformations&quot;:</span> <span class="pre">{&quot;0&quot;:</span> <span class="pre">&quot;C...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">..</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">...</span> <span class="pre">68</span>&#160;&#160;&#160; <span class="pre">SeasonalityMotif</span>&#160; <span class="pre">{\n</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">&quot;window&quot;:</span> <span class="pre">5,</span> <span class="pre">&quot;point_method&quot;:</span> <span class="pre">&quot;w...</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;nearest&quot;,</span> <span class="pre">&quot;transformations&quot;:</span> <span class="pre">{&quot;0&quot;:...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">69</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">TiDE</span>&#160; <span class="pre">{\n</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">&quot;learning_rate&quot;:</span> <span class="pre">0.000999999,</span> <span class="pre">&quot;...</span>&#160; <span class="pre">\n</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;ffill&quot;,</span> <span class="pre">&quot;transformations...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">70</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">Cassandra</span>&#160; <span class="pre">{&quot;preprocessing_transformation&quot;:</span> <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;f...</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;linear&quot;,</span> <span class="pre">&quot;transformations&quot;:</span> <span class="pre">{&quot;0&quot;:</span> <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">71</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">Cassandra</span>&#160; <span class="pre">{&quot;preprocessing_transformation&quot;:</span> <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;m...</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;pad&quot;,</span> <span class="pre">&quot;transformations&quot;:</span> <span class="pre">{&quot;0&quot;:</span> <span class="pre">&quot;EW...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">72</span>&#160;&#160;&#160;&#160;&#160; <span class="pre">NeuralForecast</span>&#160; <span class="pre">{&quot;model&quot;:</span> <span class="pre">&quot;MLP&quot;,</span> <span class="pre">&quot;scaler_type&quot;:</span> <span class="pre">&quot;minmax&quot;,</span> <span class="pre">&quot;los...</span>&#160; <span class="pre">{&quot;fillna&quot;:</span> <span class="pre">&quot;SeasonalityMotifImputerLinMix&quot;,</span> <span class="pre">&quot;t...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span>&#160; <span class="pre">[71</span> <span class="pre">rows</span> <span class="pre">x</span> <span class="pre">4</span> <span class="pre">columns]</span></em><a class="headerlink" href="#autots.templates.general.general_template" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.templates.general.</span></span><span class="sig-name descname"><span class="pre">general_template</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">Model</span>&#160; <span class="pre">...</span> <span class="pre">Ensemble</span> <span class="pre">1</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">ARIMA</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">3</span>&#160;&#160;&#160; <span class="pre">AverageValueNaive</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">4</span>&#160;&#160;&#160; <span class="pre">AverageValueNaive</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">5</span>&#160;&#160;&#160; <span class="pre">AverageValueNaive</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">6</span>&#160;&#160; <span class="pre">DatepartRegression</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">..</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">...</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160; <span class="pre">...</span> <span class="pre">68</span>&#160;&#160;&#160; <span class="pre">SeasonalityMotif</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">69</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">TiDE</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">70</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">Cassandra</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">71</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">Cassandra</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span> <span class="pre">72</span>&#160;&#160;&#160;&#160;&#160; <span class="pre">NeuralForecast</span>&#160; <span class="pre">...</span>&#160;&#160;&#160;&#160;&#160;&#160;&#160; <span class="pre">0</span>&#160; <span class="pre">[71</span> <span class="pre">rows</span> <span class="pre">x</span> <span class="pre">4</span> <span class="pre">columns]</span></em><a class="headerlink" href="#autots.templates.general.general_template" title="Link to this definition">¶</a></dt>
 <dd><p># Basic Template Construction Code
 # transformer_max_depth = 6 and transformer_list = “fast”
 from autots.evaluator.auto_model import unpack_ensemble_models
@@ -84,7 +92,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.templates">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.templates" title="Permalink to this heading">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.templates" title="Link to this heading">¶</a></h2>
 <p>Model Templates</p>
 </section>
 </section>
@@ -179,21 +187,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/source/autots.tools.html b/docs/build/html/source/autots.tools.html
index cfeee336..8144dee8 100644
--- a/docs/build/html/source/autots.tools.html
+++ b/docs/build/html/source/autots.tools.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="../">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>autots.tools package &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
-    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/doctools.js"></script>
-    <script src="../_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css?v=a4fa0645" />
+    <script src="../_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="../_static/doctools.js?v=888ff710"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script async="async" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
@@ -33,12 +41,12 @@
           <div class="body" role="main">
             
   <section id="autots-tools-package">
-<h1>autots.tools package<a class="headerlink" href="#autots-tools-package" title="Permalink to this heading">¶</a></h1>
+<h1>autots.tools package<a class="headerlink" href="#autots-tools-package" title="Link to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading">¶</a></h2>
 </section>
 <section id="module-autots.tools.anomaly_utils">
-<span id="autots-tools-anomaly-utils-module"></span><h2>autots.tools.anomaly_utils module<a class="headerlink" href="#module-autots.tools.anomaly_utils" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-anomaly-utils-module"></span><h2>autots.tools.anomaly_utils module<a class="headerlink" href="#module-autots.tools.anomaly_utils" title="Link to this heading">¶</a></h2>
 <p>Created on Fri Jul  1 15:41:21 2022</p>
 <p>&#64;author: Colin</p>
 <p>point, contextual, and collective. Point anomalies are single values
@@ -49,23 +57,23 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 regard to local values - <a class="reference external" href="https://arxiv.org/pdf/1802.04431.pdf">https://arxiv.org/pdf/1802.04431.pdf</a></p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.anomaly_df_to_holidays">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">anomaly_df_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">anomaly_df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_scores</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_occurrences</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">splash_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.65</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dayofmonth_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.anomaly_df_to_holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">anomaly_df_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">anomaly_df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">actuals</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_scores</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_occurrences</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">splash_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.65</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dayofmonth_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.anomaly_df_to_holidays" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.anomaly_new_params">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">anomaly_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.anomaly_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">anomaly_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.anomaly_new_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.create_dates_df">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">create_dates_df</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.create_dates_df" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">create_dates_df</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.create_dates_df" title="Link to this definition">¶</a></dt>
 <dd><p>Take a pd.DatetimeIndex and create simple date parts.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.dates_to_holidays">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_cols</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">style</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'long'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">day_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_features</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.dates_to_holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df_cols</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">style</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'long'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">day_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_features</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.dates_to_holidays" title="Link to this definition">¶</a></dt>
 <dd><p>Populate date information for a given pd.DatetimeIndex.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -86,7 +94,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.detect_anomalies">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">detect_anomalies</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.detect_anomalies" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">detect_anomalies</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_period</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.detect_anomalies" title="Link to this definition">¶</a></dt>
 <dd><p>All will return -1 for anomalies.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -106,39 +114,39 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.holiday_new_params">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">holiday_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.holiday_new_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">holiday_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.holiday_new_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.limits_to_anomalies">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">limits_to_anomalies</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.limits_to_anomalies" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">limits_to_anomalies</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upper_limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lower_limit</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.limits_to_anomalies" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.loop_sk_outliers">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">loop_sk_outliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.loop_sk_outliers" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">loop_sk_outliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.loop_sk_outliers" title="Link to this definition">¶</a></dt>
 <dd><p>Multiprocessing on each series for multivariate outliers with sklearn.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.nonparametric_multivariate">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">nonparametric_multivariate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.nonparametric_multivariate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">nonparametric_multivariate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.nonparametric_multivariate" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.sk_outliers">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">sk_outliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.sk_outliers" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">sk_outliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.sk_outliers" title="Link to this definition">¶</a></dt>
 <dd><p>scikit-learn outlier methods wrapper.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.values_to_anomalies">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">values_to_anomalies</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.values_to_anomalies" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">values_to_anomalies</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.values_to_anomalies" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.anomaly_utils.zscore_survival_function">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">zscore_survival_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zscore'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distribution</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'norm'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.zscore_survival_function" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.anomaly_utils.</span></span><span class="sig-name descname"><span class="pre">zscore_survival_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zscore'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distribution</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'norm'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.anomaly_utils.zscore_survival_function" title="Link to this definition">¶</a></dt>
 <dd><p>Take a dataframe and generate zscores and then generating survival probabilities (smaller = more outliery).</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -159,31 +167,31 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-autots.tools.calendar">
-<span id="autots-tools-calendar-module"></span><h2>autots.tools.calendar module<a class="headerlink" href="#module-autots.tools.calendar" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-calendar-module"></span><h2>autots.tools.calendar module<a class="headerlink" href="#module-autots.tools.calendar" title="Link to this heading">¶</a></h2>
 <p>Calendar conversion functions.</p>
 <p>Includes Lunar, Chinese lunar, and Arabic lunar</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.calendar.gregorian_to_chinese">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">gregorian_to_chinese</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetime_index</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.gregorian_to_chinese" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">gregorian_to_chinese</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetime_index</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.gregorian_to_chinese" title="Link to this definition">¶</a></dt>
 <dd><p>Convert a pandas DatetimeIndex to Chinese Lunar calendar. Potentially has errors.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.calendar.gregorian_to_christian_lunar">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">gregorian_to_christian_lunar</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetime_index</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.gregorian_to_christian_lunar" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">gregorian_to_christian_lunar</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetime_index</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.gregorian_to_christian_lunar" title="Link to this definition">¶</a></dt>
 <dd><p>Convert a pandas DatetimeIndex to Christian Lunar calendar. Aspiration it doesn’t work exactly.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.calendar.gregorian_to_hebrew">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">gregorian_to_hebrew</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.gregorian_to_hebrew" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">gregorian_to_hebrew</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.gregorian_to_hebrew" title="Link to this definition">¶</a></dt>
 <dd><p>Convert pd.Datetimes to a Hebrew date. From pyluach by simlist.</p>
 <p>This is the slowest of the lot and needs to be improved.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.calendar.gregorian_to_islamic">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">gregorian_to_islamic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">date</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch_adjustment</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.gregorian_to_islamic" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">gregorian_to_islamic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">date</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch_adjustment</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.5</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.gregorian_to_islamic" title="Link to this definition">¶</a></dt>
 <dd><p>Calculate Islamic dates for pandas DatetimeIndex. Approximately. From convertdate by fitnr.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -194,50 +202,50 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.calendar.heb_is_leap">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">heb_is_leap</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">year</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.heb_is_leap" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">heb_is_leap</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">year</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.heb_is_leap" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.calendar.lunar_from_lunar">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">lunar_from_lunar</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">new_moon</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.lunar_from_lunar" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">lunar_from_lunar</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">new_moon</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.lunar_from_lunar" title="Link to this definition">¶</a></dt>
 <dd><p>Assumes continuous daily data and pre-needed start.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.calendar.lunar_from_lunar_full">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">lunar_from_lunar_full</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">full_moon</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.lunar_from_lunar_full" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">lunar_from_lunar_full</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">full_moon</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.lunar_from_lunar_full" title="Link to this definition">¶</a></dt>
 <dd><p>Assumes continuous daily data and pre-needed start.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.calendar.to_jd">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">to_jd</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">year</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">month</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">day</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.to_jd" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.calendar.</span></span><span class="sig-name descname"><span class="pre">to_jd</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">year</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">month</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">day</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.calendar.to_jd" title="Link to this definition">¶</a></dt>
 <dd><p>Determine Julian day count from Islamic date. From convertdate by fitnr.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.tools.cointegration">
-<span id="autots-tools-cointegration-module"></span><h2>autots.tools.cointegration module<a class="headerlink" href="#module-autots.tools.cointegration" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-cointegration-module"></span><h2>autots.tools.cointegration module<a class="headerlink" href="#module-autots.tools.cointegration" title="Link to this heading">¶</a></h2>
 <p>Cointegration</p>
 <p>Johansen heavily based on Statsmodels source code</p>
 <p>BTCD heavily based on D. Barba
 <a class="reference external" href="https://towardsdatascience.com/canonical-decomposition-a-forgotten-method-for-time-series-cointegration-and-beyond-4d1213396da1">https://towardsdatascience.com/canonical-decomposition-a-forgotten-method-for-time-series-cointegration-and-beyond-4d1213396da1</a></p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.cointegration.btcd_decompose">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.cointegration.</span></span><span class="sig-name descname"><span class="pre">btcd_decompose</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p_mat</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_eigenvalues</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cointegration.btcd_decompose" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.cointegration.</span></span><span class="sig-name descname"><span class="pre">btcd_decompose</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p_mat</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_eigenvalues</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cointegration.btcd_decompose" title="Link to this definition">¶</a></dt>
 <dd><p>Calculate decomposition.
 p_mat is of shape(t,n), wide style data.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.cointegration.coint_johansen">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.cointegration.</span></span><span class="sig-name descname"><span class="pre">coint_johansen</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">endog</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">det_order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_ar_diff</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_eigenvalues</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cointegration.coint_johansen" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.cointegration.</span></span><span class="sig-name descname"><span class="pre">coint_johansen</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">endog</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">det_order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_ar_diff</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_eigenvalues</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cointegration.coint_johansen" title="Link to this definition">¶</a></dt>
 <dd><p>Johansen cointegration test of the cointegration rank of a VECM, abbreviated from Statsmodels</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.cointegration.fourier_series">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.cointegration.</span></span><span class="sig-name descname"><span class="pre">fourier_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">period</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_order</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cointegration.fourier_series" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.cointegration.</span></span><span class="sig-name descname"><span class="pre">fourier_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">period</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series_order</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cointegration.fourier_series" title="Link to this definition">¶</a></dt>
 <dd><p>Provides Fourier series components with the specified frequency
 and order.</p>
 <dl class="field-list simple">
@@ -256,17 +264,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.cointegration.lagmat">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.cointegration.</span></span><span class="sig-name descname"><span class="pre">lagmat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxlag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forward'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">original</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'ex'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cointegration.lagmat" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.cointegration.</span></span><span class="sig-name descname"><span class="pre">lagmat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxlag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'forward'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">original</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'ex'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cointegration.lagmat" title="Link to this definition">¶</a></dt>
 <dd><p>Create 2d array of lags. Modified from Statsmodels.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.tools.cpu_count">
-<span id="autots-tools-cpu-count-module"></span><h2>autots.tools.cpu_count module<a class="headerlink" href="#module-autots.tools.cpu_count" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-cpu-count-module"></span><h2>autots.tools.cpu_count module<a class="headerlink" href="#module-autots.tools.cpu_count" title="Link to this heading">¶</a></h2>
 <p>CPU counter for multiprocesing.</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.cpu_count.cpu_count">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.cpu_count.</span></span><span class="sig-name descname"><span class="pre">cpu_count</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">modifier</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cpu_count.cpu_count" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.cpu_count.</span></span><span class="sig-name descname"><span class="pre">cpu_count</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">modifier</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cpu_count.cpu_count" title="Link to this definition">¶</a></dt>
 <dd><p>Find available CPU count, running on both Windows/Linux.</p>
 <dl class="simple">
 <dt>Attempts to be very conservative:</dt><dd><ul class="simple">
@@ -285,12 +293,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.cpu_count.set_n_jobs">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.cpu_count.</span></span><span class="sig-name descname"><span class="pre">set_n_jobs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cpu_count.set_n_jobs" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.cpu_count.</span></span><span class="sig-name descname"><span class="pre">set_n_jobs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.cpu_count.set_n_jobs" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.tools.fast_kalman">
-<span id="autots-tools-fast-kalman-module"></span><h2>autots.tools.fast_kalman module<a class="headerlink" href="#module-autots.tools.fast_kalman" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-fast-kalman-module"></span><h2>autots.tools.fast_kalman module<a class="headerlink" href="#module-autots.tools.fast_kalman" title="Link to this heading">¶</a></h2>
 <p>From SIMD KALMAN, (c) 2017 Otto Seiskari (MIT License)</p>
 <dl class="simple">
 <dt>Some other resources that I have found useful:</dt><dd><p><a class="reference external" href="https://kevinkotze.github.io/ts-4-state-space/">https://kevinkotze.github.io/ts-4-state-space/</a>
@@ -318,7 +326,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </aside>
 </aside>
 <section id="usage-example">
-<h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to this heading">¶</a></h3>
+<h3>Usage example<a class="headerlink" href="#usage-example" title="Link to this heading">¶</a></h3>
 <blockquote>
 <div><p>import numpy.random
 numpy.random.seed(0)</p>
@@ -383,28 +391,28 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </section>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.Gaussian">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">Gaussian</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cov</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.Gaussian" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">Gaussian</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cov</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.Gaussian" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.Gaussian.empty">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">empty</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_states</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_vars</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_measurements</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cov</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.Gaussian.empty" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">empty</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_states</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_vars</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_measurements</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cov</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.Gaussian.empty" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.Gaussian.unvectorize_state">
-<span class="sig-name descname"><span class="pre">unvectorize_state</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.Gaussian.unvectorize_state" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">unvectorize_state</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.Gaussian.unvectorize_state" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.Gaussian.unvectorize_vars">
-<span class="sig-name descname"><span class="pre">unvectorize_vars</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.Gaussian.unvectorize_vars" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">unvectorize_vars</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.Gaussian.unvectorize_vars" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">KalmanFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">state_transition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">KalmanFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">state_transition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>The main Kalman filter class providing convenient interfaces to
 vectorized smoothing and filtering operations on multiple independent
@@ -434,13 +442,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.Result">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Result</span></span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.Result" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Result</span></span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.Result" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.compute">
-<span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_covariance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">smoothed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filtered</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">states</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariances</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">likelihoods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gains</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">log_likelihood</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.compute" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_covariance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">smoothed</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filtered</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">states</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariances</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">likelihoods</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gains</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">log_likelihood</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.compute" title="Link to this definition">¶</a></dt>
 <dd><p>Smoothing, filtering and prediction at the same time. Used internally
 by other methods, but can also be used directly if, e.g., both smoothed
 and predicted data is wanted.</p>
@@ -474,22 +482,22 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.em">
-<span class="sig-name descname"><span class="pre">em</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_iter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_covariance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.em" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">em</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_iter</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_covariance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.em" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.em_observation_noise">
-<span class="sig-name descname"><span class="pre">em_observation_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.em_observation_noise" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">em_observation_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.em_observation_noise" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.em_process_noise">
-<span class="sig-name descname"><span class="pre">em_process_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.em_process_noise" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">em_process_noise</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.em_process_noise" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_covariance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">states</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariances</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_test</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_covariance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">states</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariances</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Filter past data and predict a given number of future values.
 The data can be given as either of</p>
 <blockquote>
@@ -533,7 +541,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.predict_next">
-<span class="sig-name descname"><span class="pre">predict_next</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.predict_next" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_next</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.predict_next" title="Link to this definition">¶</a></dt>
 <dd><p>Single prediction step</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -551,7 +559,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.predict_observation">
-<span class="sig-name descname"><span class="pre">predict_observation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.predict_observation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict_observation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.predict_observation" title="Link to this definition">¶</a></dt>
 <dd><p>Probability distribution of observation <span class="math notranslate nohighlight">\(y\)</span> for a given
 distribution of <span class="math notranslate nohighlight">\(x\)</span></p>
 <dl class="field-list simple">
@@ -570,7 +578,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.smooth">
-<span class="sig-name descname"><span class="pre">smooth</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_covariance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">states</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariances</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.smooth" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">smooth</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_covariance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observations</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">states</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariances</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.smooth" title="Link to this definition">¶</a></dt>
 <dd><p>Smooth given data, which can be either</p>
 <blockquote>
 <div><ul class="simple">
@@ -612,7 +620,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.smooth_current">
-<span class="sig-name descname"><span class="pre">smooth_current</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ms</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Ps</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.smooth_current" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">smooth_current</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ms</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Ps</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.smooth_current" title="Link to this definition">¶</a></dt>
 <dd><p>Simgle Kalman smoother backwards step</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -636,7 +644,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.KalmanFilter.update">
-<span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">log_likelihood</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.update" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">log_likelihood</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.KalmanFilter.update" title="Link to this definition">¶</a></dt>
 <dd><p>Single update step with NaN check.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -663,64 +671,64 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.autoshape">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">autoshape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.autoshape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">autoshape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.autoshape" title="Link to this definition">¶</a></dt>
 <dd><p>Automatically shape arguments and return values</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.ddot">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">ddot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">B</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.ddot" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">ddot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">B</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.ddot" title="Link to this definition">¶</a></dt>
 <dd><p>Matrix multiplication over last two axes</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.ddot_t_right">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">ddot_t_right</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">B</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.ddot_t_right" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">ddot_t_right</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">B</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.ddot_t_right" title="Link to this definition">¶</a></dt>
 <dd><p>Matrix multiplication over last 2 axes with right operand transposed</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.ddot_t_right_old">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">ddot_t_right_old</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">B</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.ddot_t_right_old" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">ddot_t_right_old</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">B</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.ddot_t_right_old" title="Link to this definition">¶</a></dt>
 <dd><p>Matrix multiplication over last 2 axes with right operand transposed</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.dinv">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">dinv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.dinv" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">dinv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">A</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.dinv" title="Link to this definition">¶</a></dt>
 <dd><p>Matrix inverse applied to last two axes</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.douter">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">douter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">b</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.douter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">douter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">b</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.douter" title="Link to this definition">¶</a></dt>
 <dd><p>Outer product, last two axes</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.em_initial_state">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">em_initial_state</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_means</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.em_initial_state" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">em_initial_state</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_means</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.em_initial_state" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.ensure_matrix">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">ensure_matrix</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.ensure_matrix" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">ensure_matrix</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.ensure_matrix" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.holt_winters_damped_matrices">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">holt_winters_damped_matrices</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">M</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">beta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.holt_winters_damped_matrices" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">holt_winters_damped_matrices</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">M</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">beta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.holt_winters_damped_matrices" title="Link to this definition">¶</a></dt>
 <dd><p>Not sure if this is correct. It’s close, at least.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.new_kalman_params">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">new_kalman_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_auto</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.new_kalman_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">new_kalman_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_auto</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.new_kalman_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.predict">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state_transition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state_transition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.predict" title="Link to this definition">¶</a></dt>
 <dd><p>Kalman filter prediction step</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -742,7 +750,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.predict_observation">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">predict_observation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.predict_observation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">predict_observation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.predict_observation" title="Link to this definition">¶</a></dt>
 <dd><p>Compute probability distribution of the observation <span class="math notranslate nohighlight">\(y\)</span>, given
 the distribution of <span class="math notranslate nohighlight">\(x\)</span>.</p>
 <dl class="field-list simple">
@@ -762,23 +770,23 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.priv_smooth">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">priv_smooth</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">posterior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">posterior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state_transition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">next_smooth_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">next_smooth_covariance</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.priv_smooth" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">priv_smooth</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">posterior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">posterior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state_transition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">next_smooth_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">next_smooth_covariance</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.priv_smooth" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.priv_update_with_nan_check">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">priv_update_with_nan_check</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">log_likelihood</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.priv_update_with_nan_check" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">priv_update_with_nan_check</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">log_likelihood</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.priv_update_with_nan_check" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.random_state_space">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">random_state_space</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.random_state_space" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">random_state_space</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.random_state_space" title="Link to this definition">¶</a></dt>
 <dd><p>Return randomly generated statespace models.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.smooth">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">smooth</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">posterior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">posterior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state_transition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">next_smooth_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">next_smooth_covariance</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.smooth" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">smooth</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">posterior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">posterior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state_transition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">next_smooth_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">next_smooth_covariance</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.smooth" title="Link to this definition">¶</a></dt>
 <dd><p>Kalman smoother backwards step</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -803,7 +811,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.update">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.update" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.update" title="Link to this definition">¶</a></dt>
 <dd><p>Kalman filter update step</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -829,43 +837,43 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fast_kalman.update_with_nan_check">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">update_with_nan_check</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.update_with_nan_check" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fast_kalman.</span></span><span class="sig-name descname"><span class="pre">update_with_nan_check</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prior_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prior_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fast_kalman.update_with_nan_check" title="Link to this definition">¶</a></dt>
 <dd><p>Kalman filter update with a check for NaN observations. Like <code class="docutils literal notranslate"><span class="pre">update</span></code> but
 returns <code class="docutils literal notranslate"><span class="pre">(prior_mean,</span> <span class="pre">prior_covariance)</span></code> if <code class="docutils literal notranslate"><span class="pre">measurement</span></code> is NaN</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.tools.fft">
-<span id="autots-tools-fft-module"></span><h2>autots.tools.fft module<a class="headerlink" href="#module-autots.tools.fft" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-fft-module"></span><h2>autots.tools.fft module<a class="headerlink" href="#module-autots.tools.fft" title="Link to this heading">¶</a></h2>
 <p>Created on Mon Oct  9 22:07:37 2023</p>
 <p>&#64;author: colincatlin</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.fft.FFT">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.fft.</span></span><span class="sig-name descname"><span class="pre">FFT</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_harm</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detrend</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">freq_range</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fft.FFT" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.fft.</span></span><span class="sig-name descname"><span class="pre">FFT</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_harm</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detrend</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">freq_range</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fft.FFT" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fft.FFT.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fft.FFT.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fft.FFT.fit" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.fft.FFT.predict">
-<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fft.FFT.predict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fft.FFT.predict" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.fft.fourier_extrapolation">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.fft.</span></span><span class="sig-name descname"><span class="pre">fourier_extrapolation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_harm</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detrend</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">freq_range</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fft.fourier_extrapolation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.fft.</span></span><span class="sig-name descname"><span class="pre">fourier_extrapolation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_harm</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detrend</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">freq_range</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.fft.fourier_extrapolation" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.tools.hierarchial">
-<span id="autots-tools-hierarchial-module"></span><h2>autots.tools.hierarchial module<a class="headerlink" href="#module-autots.tools.hierarchial" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-hierarchial-module"></span><h2>autots.tools.hierarchial module<a class="headerlink" href="#module-autots.tools.hierarchial" title="Link to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.hierarchial.hierarchial">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.hierarchial.</span></span><span class="sig-name descname"><span class="pre">hierarchial</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">grouping_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'tile'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_groups</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reconciliation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.hierarchial.hierarchial" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.hierarchial.</span></span><span class="sig-name descname"><span class="pre">hierarchial</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">grouping_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'tile'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_groups</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reconciliation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.hierarchial.hierarchial" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Create hierarchial series, then reconcile.</p>
 <p>Currently only performs one-level groupings.
@@ -879,19 +887,19 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 :type grouping_ids: dict</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.hierarchial.hierarchial.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.hierarchial.hierarchial.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.hierarchial.hierarchial.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Construct and save object info.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.hierarchial.hierarchial.reconcile">
-<span class="sig-name descname"><span class="pre">reconcile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.hierarchial.hierarchial.reconcile" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">reconcile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.hierarchial.hierarchial.reconcile" title="Link to this definition">¶</a></dt>
 <dd><p>Apply to forecasted data containing bottom and top levels.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.hierarchial.hierarchial.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.hierarchial.hierarchial.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.hierarchial.hierarchial.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Apply hierarchy to existing data with bottom levels only.</p>
 </dd></dl>
 
@@ -899,11 +907,11 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 </section>
 <section id="module-autots.tools.holiday">
-<span id="autots-tools-holiday-module"></span><h2>autots.tools.holiday module<a class="headerlink" href="#module-autots.tools.holiday" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-holiday-module"></span><h2>autots.tools.holiday module<a class="headerlink" href="#module-autots.tools.holiday" title="Link to this heading">¶</a></h2>
 <p>Manage holiday features.</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.holiday.holiday_flag">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.holiday.</span></span><span class="sig-name descname"><span class="pre">holiday_flag</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encode_holiday_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holidays_subdiv</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.holiday.holiday_flag" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.holiday.</span></span><span class="sig-name descname"><span class="pre">holiday_flag</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encode_holiday_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holidays_subdiv</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.holiday.holiday_flag" title="Link to this definition">¶</a></dt>
 <dd><p>Create a 0/1 flag for given datetime index. Includes fallback to pandas for US holidays if holidays package unavailable.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -923,7 +931,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.holiday.query_holidays">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.holiday.</span></span><span class="sig-name descname"><span class="pre">query_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encode_holiday_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holidays_subdiv</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.holiday.query_holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.holiday.</span></span><span class="sig-name descname"><span class="pre">query_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encode_holiday_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holidays_subdiv</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.holiday.query_holidays" title="Link to this definition">¶</a></dt>
 <dd><p>Query holidays package for dates.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -938,11 +946,11 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 </section>
 <section id="module-autots.tools.impute">
-<span id="autots-tools-impute-module"></span><h2>autots.tools.impute module<a class="headerlink" href="#module-autots.tools.impute" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-impute-module"></span><h2>autots.tools.impute module<a class="headerlink" href="#module-autots.tools.impute" title="Link to this heading">¶</a></h2>
 <p>Fill NA.</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.FillNA">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">FillNA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.FillNA" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">FillNA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.FillNA" title="Link to this definition">¶</a></dt>
 <dd><p>Fill NA values using different methods.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -963,11 +971,11 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.impute.SeasonalityMotifImputer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">SeasonalityMotifImputer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple_2'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'canberra'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_mixed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.SeasonalityMotifImputer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">SeasonalityMotifImputer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple_2'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'canberra'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_mixed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.SeasonalityMotifImputer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.impute.SeasonalityMotifImputer.impute">
-<span class="sig-name descname"><span class="pre">impute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.SeasonalityMotifImputer.impute" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">impute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.SeasonalityMotifImputer.impute" title="Link to this definition">¶</a></dt>
 <dd><p>Infer missing values on input df.</p>
 </dd></dl>
 
@@ -975,11 +983,11 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.impute.SimpleSeasonalityMotifImputer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">SimpleSeasonalityMotifImputer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple_2'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'canberra'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_mixed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.SimpleSeasonalityMotifImputer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">SimpleSeasonalityMotifImputer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple_2'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'canberra'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_mixed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.SimpleSeasonalityMotifImputer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.impute.SimpleSeasonalityMotifImputer.impute">
-<span class="sig-name descname"><span class="pre">impute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.SimpleSeasonalityMotifImputer.impute" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">impute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.SimpleSeasonalityMotifImputer.impute" title="Link to this definition">¶</a></dt>
 <dd><p>Infer missing values on input df.</p>
 </dd></dl>
 
@@ -987,13 +995,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.biased_ffill">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">biased_ffill</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.biased_ffill" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">biased_ffill</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.biased_ffill" title="Link to this definition">¶</a></dt>
 <dd><p>Fill NaN with average of last value and mean.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fake_date_fill">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fake_date_fill</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">back_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'slice'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fake_date_fill" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fake_date_fill</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">back_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'slice'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fake_date_fill" title="Link to this definition">¶</a></dt>
 <dd><p>Numpy vectorized version.
 Return a dataframe where na values are removed and values shifted forward.</p>
 <div class="admonition warning">
@@ -1013,7 +1021,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fake_date_fill_old">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fake_date_fill_old</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">back_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'slice'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fake_date_fill_old" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fake_date_fill_old</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">back_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'slice'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fake_date_fill_old" title="Link to this definition">¶</a></dt>
 <dd><p>Return a dataframe where na values are removed and values shifted forward.</p>
 <div class="admonition warning">
 <p class="admonition-title">Warning</p>
@@ -1032,93 +1040,93 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fill_forward">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_forward</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_forward" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_forward</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_forward" title="Link to this definition">¶</a></dt>
 <dd><p>Fill NaN with previous values.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fill_forward_alt">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_forward_alt</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_forward_alt" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_forward_alt</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_forward_alt" title="Link to this definition">¶</a></dt>
 <dd><p>Fill NaN with previous values.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fill_mean">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_mean" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_mean" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fill_mean_old">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_mean_old</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_mean_old" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_mean_old</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_mean_old" title="Link to this definition">¶</a></dt>
 <dd><p>Fill NaN with mean.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fill_median">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_median</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_median" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_median</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_median" title="Link to this definition">¶</a></dt>
 <dd><p>Fill nan with median values. Does not work with non-numeric types.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fill_median_old">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_median_old</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_median_old" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_median_old</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_median_old" title="Link to this definition">¶</a></dt>
 <dd><p>Fill NaN with median.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fill_zero">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_zero</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_zero" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fill_zero</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fill_zero" title="Link to this definition">¶</a></dt>
 <dd><p>Fill NaN with zero.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.fillna_np">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fillna_np</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">values</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fillna_np" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">fillna_np</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">values</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.fillna_np" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.impute.rolling_mean">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">rolling_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.rolling_mean" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.impute.</span></span><span class="sig-name descname"><span class="pre">rolling_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.impute.rolling_mean" title="Link to this definition">¶</a></dt>
 <dd><p>Fill NaN with mean of last window values.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.tools.lunar">
-<span id="autots-tools-lunar-module"></span><h2>autots.tools.lunar module<a class="headerlink" href="#module-autots.tools.lunar" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-lunar-module"></span><h2>autots.tools.lunar module<a class="headerlink" href="#module-autots.tools.lunar" title="Link to this heading">¶</a></h2>
 <p>Phases of the moon.
 Modified from <a class="reference external" href="https://stackoverflow.com/a/2531541/9492254">https://stackoverflow.com/a/2531541/9492254</a>
 by keturn and earlier from John Walker</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.dcos">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">dcos</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.dcos" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">dcos</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.dcos" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.dsin">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">dsin</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.dsin" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">dsin</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.dsin" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.fixangle">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">fixangle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.fixangle" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">fixangle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.fixangle" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.kepler">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">kepler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ecc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.016718</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.kepler" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">kepler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">m</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ecc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.016718</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.kepler" title="Link to this definition">¶</a></dt>
 <dd><p>Solve the equation of Kepler.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.moon_phase">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">moon_phase</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetime_index</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1e-06</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2444237.905</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ecliptic_longitude_epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">278.83354</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ecliptic_longitude_perigee</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">282.596403</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eccentricity</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.016718</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">moon_mean_longitude_epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">64.975464</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">moon_mean_perigee_epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">349.383063</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.moon_phase" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">moon_phase</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetime_index</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epsilon</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1e-06</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2444237.905</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ecliptic_longitude_epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">278.83354</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ecliptic_longitude_perigee</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">282.596403</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eccentricity</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.016718</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">moon_mean_longitude_epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">64.975464</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">moon_mean_perigee_epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">349.383063</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.moon_phase" title="Link to this definition">¶</a></dt>
 <dd><p>Numpy version. Takes a pd.DatetimeIndex and returns moon phase (%illuminated).
 Epoch can be adjust slightly (0.5 = half day) to adjust for time zones. This is for US. epoch=2444238.5 for Asia generally.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.moon_phase_df">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">moon_phase_df</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetime_index</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2444237.905</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.moon_phase_df" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">moon_phase_df</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">datetime_index</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2444237.905</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.moon_phase_df" title="Link to this definition">¶</a></dt>
 <dd><p>Convert pandas DatetimeIndex to moon phases. Note timezone and hour can matter slightly.
 Epoch can be adjust slightly (0.5 = half day) to adjust for time zones.
 2444237.905 is for US Central. epoch=2444238.5 for Asia generally.</p>
@@ -1126,27 +1134,27 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.phase_string">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">phase_string</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">precision</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">first</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.75</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nextnew</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.phase_string" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">phase_string</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">precision</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">first</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.75</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nextnew</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.phase_string" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.todeg">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">todeg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">r</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.todeg" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">todeg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">r</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.todeg" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.lunar.torad">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">torad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.torad" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.lunar.</span></span><span class="sig-name descname"><span class="pre">torad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.lunar.torad" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.tools.percentile">
-<span id="autots-tools-percentile-module"></span><h2>autots.tools.percentile module<a class="headerlink" href="#module-autots.tools.percentile" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-percentile-module"></span><h2>autots.tools.percentile module<a class="headerlink" href="#module-autots.tools.percentile" title="Link to this heading">¶</a></h2>
 <p>Faster percentile and quantile for numpy</p>
 <p>Entirely from: <a class="reference external" href="https://krstn.eu/np.nanpercentile()-there-has-to-be-a-faster-way/">https://krstn.eu/np.nanpercentile()-there-has-to-be-a-faster-way/</a></p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.percentile.nan_percentile">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.percentile.</span></span><span class="sig-name descname"><span class="pre">nan_percentile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">in_arr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">errors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'raise'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.percentile.nan_percentile" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.percentile.</span></span><span class="sig-name descname"><span class="pre">nan_percentile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">in_arr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">errors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'raise'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.percentile.nan_percentile" title="Link to this definition">¶</a></dt>
 <dd><p>Given a 3D array, return the given percentiles as input by q.
 Beware this is only tested for the limited case required here, and will not match np fully.
 Args more limited. If errors=”rollover” passes to np.nanpercentile where args are not supported.</p>
@@ -1154,23 +1162,23 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.percentile.nan_quantile">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.percentile.</span></span><span class="sig-name descname"><span class="pre">nan_quantile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">errors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'raise'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.percentile.nan_quantile" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.percentile.</span></span><span class="sig-name descname"><span class="pre">nan_quantile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">q</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">errors</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'raise'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.percentile.nan_quantile" title="Link to this definition">¶</a></dt>
 <dd><p>Same as nan_percentile but accepts q in range [0, 1].
 Args more limited. If errors=”rollover” passes to np.nanpercentile where not supported.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.percentile.trimmed_mean">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.percentile.</span></span><span class="sig-name descname"><span class="pre">trimmed_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percent</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.percentile.trimmed_mean" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.percentile.</span></span><span class="sig-name descname"><span class="pre">trimmed_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percent</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.percentile.trimmed_mean" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.tools.probabilistic">
-<span id="autots-tools-probabilistic-module"></span><h2>autots.tools.probabilistic module<a class="headerlink" href="#module-autots.tools.probabilistic" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-probabilistic-module"></span><h2>autots.tools.probabilistic module<a class="headerlink" href="#module-autots.tools.probabilistic" title="Link to this heading">¶</a></h2>
 <p>Point to Probabilistic</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.probabilistic.Point_to_Probability">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">Point_to_Probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'historic_quantile'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.Point_to_Probability" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">Point_to_Probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'historic_quantile'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.Point_to_Probability" title="Link to this definition">¶</a></dt>
 <dd><p>Data driven placeholder for model error estimation.</p>
 <p>Catlin Point to Probability method (‘a mixture of dark magic and gum disease’)</p>
 <dl class="field-list simple">
@@ -1194,7 +1202,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.probabilistic.Variable_Point_to_Probability">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">Variable_Point_to_Probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">beta</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.Variable_Point_to_Probability" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">Variable_Point_to_Probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">beta</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.Variable_Point_to_Probability" title="Link to this definition">¶</a></dt>
 <dd><p>Data driven placeholder for model error estimation.</p>
 <p>ErrorRange = beta * (En + alpha * En-1 [cum sum of En])
 En = abs(0.5 - QTP) * D
@@ -1226,7 +1234,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.probabilistic.historic_quantile">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">historic_quantile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.historic_quantile" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">historic_quantile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.historic_quantile" title="Link to this definition">¶</a></dt>
 <dd><p>Computes the difference between the median and the prediction interval range in historic data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1246,33 +1254,33 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.probabilistic.inferred_normal">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">inferred_normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.inferred_normal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">inferred_normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prediction_interval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.9</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.inferred_normal" title="Link to this definition">¶</a></dt>
 <dd><p>A corruption of Bayes theorem.
 It will be sensitive to the transformations of the data.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.probabilistic.percentileofscore_appliable">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">percentileofscore_appliable</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">a</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'rank'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.percentileofscore_appliable" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.probabilistic.</span></span><span class="sig-name descname"><span class="pre">percentileofscore_appliable</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">a</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'rank'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.probabilistic.percentileofscore_appliable" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.tools.profile">
-<span id="autots-tools-profile-module"></span><h2>autots.tools.profile module<a class="headerlink" href="#module-autots.tools.profile" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-profile-module"></span><h2>autots.tools.profile module<a class="headerlink" href="#module-autots.tools.profile" title="Link to this heading">¶</a></h2>
 <p>Profiling</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.profile.data_profile">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.profile.</span></span><span class="sig-name descname"><span class="pre">data_profile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.profile.data_profile" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.profile.</span></span><span class="sig-name descname"><span class="pre">data_profile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.profile.data_profile" title="Link to this definition">¶</a></dt>
 <dd><p>Input: a pd DataFrame of columns which are time series, and a datetime index</p>
 <p>Output: a pd DataFrame of column per time series, with rows which are statistics</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.tools.regressor">
-<span id="autots-tools-regressor-module"></span><h2>autots.tools.regressor module<a class="headerlink" href="#module-autots.tools.regressor" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-regressor-module"></span><h2>autots.tools.regressor module<a class="headerlink" href="#module-autots.tools.regressor" title="Link to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.regressor.create_lagged_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.regressor.</span></span><span class="sig-name descname"><span class="pre">create_lagged_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">summarize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">backfill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bfill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.regressor.create_lagged_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.regressor.</span></span><span class="sig-name descname"><span class="pre">create_lagged_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">summarize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">backfill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bfill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.regressor.create_lagged_regressor" title="Link to this definition">¶</a></dt>
 <dd><p>Create a regressor of features lagged by forecast length.
 Useful to some models that don’t otherwise use such information.</p>
 <p>It is recommended that the .head(forecast_length) of both regressor_train and the df for training are dropped.
@@ -1301,7 +1309,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.regressor.create_regressor">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.regressor.</span></span><span class="sig-name descname"><span class="pre">create_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['US']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple_binarized'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">summarize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">backfill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bfill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encode_holiday_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'anomaly_detector_params':</span> <span class="pre">{'forecast_params':</span> <span class="pre">None,</span> <span class="pre">'method':</span> <span class="pre">'mad',</span> <span class="pre">'method_params':</span> <span class="pre">{'alpha':</span> <span class="pre">0.05,</span> <span class="pre">'distribution':</span> <span class="pre">'gamma'},</span> <span class="pre">'transform_dict':</span> <span class="pre">{'fillna':</span> <span class="pre">None,</span> <span class="pre">'transformation_params':</span> <span class="pre">{'0':</span> <span class="pre">{}},</span> <span class="pre">'transformations':</span> <span class="pre">{'0':</span> <span class="pre">'DifferencedTransformer'}}},</span> <span class="pre">'output':</span> <span class="pre">'univariate',</span> <span class="pre">'splash_threshold':</span> <span class="pre">None,</span> <span class="pre">'threshold':</span> <span class="pre">0.8,</span> <span class="pre">'use_dayofmonth_holidays':</span> <span class="pre">True,</span> <span class="pre">'use_hebrew_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_islamic_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_lunar_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_lunar_weekday':</span> <span class="pre">False,</span> <span class="pre">'use_wkdeom_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_wkdom_holidays':</span> <span class="pre">True}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_regr_style</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preprocessing_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.regressor.create_regressor" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.regressor.</span></span><span class="sig-name descname"><span class="pre">create_regressor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['US']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple_binarized'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">summarize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">backfill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bfill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encode_holiday_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'anomaly_detector_params':</span> <span class="pre">{'forecast_params':</span> <span class="pre">None,</span> <span class="pre">'method':</span> <span class="pre">'mad',</span> <span class="pre">'method_params':</span> <span class="pre">{'alpha':</span> <span class="pre">0.05,</span> <span class="pre">'distribution':</span> <span class="pre">'gamma'},</span> <span class="pre">'transform_dict':</span> <span class="pre">{'fillna':</span> <span class="pre">None,</span> <span class="pre">'transformation_params':</span> <span class="pre">{'0':</span> <span class="pre">{}},</span> <span class="pre">'transformations':</span> <span class="pre">{'0':</span> <span class="pre">'DifferencedTransformer'}}},</span> <span class="pre">'output':</span> <span class="pre">'univariate',</span> <span class="pre">'splash_threshold':</span> <span class="pre">None,</span> <span class="pre">'threshold':</span> <span class="pre">0.8,</span> <span class="pre">'use_dayofmonth_holidays':</span> <span class="pre">True,</span> <span class="pre">'use_hebrew_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_islamic_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_lunar_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_lunar_weekday':</span> <span class="pre">False,</span> <span class="pre">'use_wkdeom_holidays':</span> <span class="pre">False,</span> <span class="pre">'use_wkdom_holidays':</span> <span class="pre">True}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_regr_style</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">preprocessing_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.regressor.create_regressor" title="Link to this definition">¶</a></dt>
 <dd><p>Create a regressor from information available in the existing dataset.
 Components: are lagged data, datepart information, and holiday.</p>
 <p>This function has been confusing people. This is NOT necessary for machine learning models, in AutoTS they internally create more elaborate feature sets separately.
@@ -1343,24 +1351,24 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 </section>
 <section id="module-autots.tools.seasonal">
-<span id="autots-tools-seasonal-module"></span><h2>autots.tools.seasonal module<a class="headerlink" href="#module-autots.tools.seasonal" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-seasonal-module"></span><h2>autots.tools.seasonal module<a class="headerlink" href="#module-autots.tools.seasonal" title="Link to this heading">¶</a></h2>
 <p>seasonal</p>
 <p>&#64;author: Colin</p>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.create_datepart_components">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">create_datepart_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.create_datepart_components" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">create_datepart_components</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.create_datepart_components" title="Link to this definition">¶</a></dt>
 <dd><p>single date part one-hot flags.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.create_seasonality_feature">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">create_seasonality_feature</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">history_days</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.create_seasonality_feature" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">create_seasonality_feature</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">history_days</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.create_seasonality_feature" title="Link to this definition">¶</a></dt>
 <dd><p>Cassandra-designed feature generator.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.date_part">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">date_part</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">set_index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.date_part" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">date_part</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'simple'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">set_index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.date_part" title="Link to this definition">¶</a></dt>
 <dd><p>Create date part columns from pd.DatetimeIndex.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1387,28 +1395,28 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.fourier_df">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">fourier_df</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">history_days</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.fourier_df" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">fourier_df</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">history_days</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.fourier_df" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.fourier_series">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">fourier_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">t</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">365.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.fourier_series" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">fourier_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">t</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">365.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.fourier_series" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.random_datepart">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">random_datepart</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.random_datepart" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">random_datepart</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.random_datepart" title="Link to this definition">¶</a></dt>
 <dd><p>New random parameters for seasonality.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.seasonal_independent_match">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">seasonal_independent_match</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">DTindex_future</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'simple_binarized'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'canberra'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_sort</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.seasonal_independent_match" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">seasonal_independent_match</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">DTindex_future</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'simple_binarized'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'canberra'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_sort</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_array</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.seasonal_independent_match" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.seasonal_int">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">seasonal_int</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">include_one</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">small</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">very_small</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.seasonal_int" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">seasonal_int</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">include_one</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">small</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">very_small</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.seasonal_int" title="Link to this definition">¶</a></dt>
 <dd><p>Generate a random integer of typical seasonalities.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1423,16 +1431,16 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.seasonal.seasonal_window_match">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">seasonal_window_match</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_sort</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.seasonal_window_match" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.seasonal.</span></span><span class="sig-name descname"><span class="pre">seasonal_window_match</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">DTindex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">full_sort</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.seasonal.seasonal_window_match" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.tools.shaping">
-<span id="autots-tools-shaping-module"></span><h2>autots.tools.shaping module<a class="headerlink" href="#module-autots.tools.shaping" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-shaping-module"></span><h2>autots.tools.shaping module<a class="headerlink" href="#module-autots.tools.shaping" title="Link to this heading">¶</a></h2>
 <p>Reshape data.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.shaping.NumericTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">NumericTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">na_strings</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['',</span> <span class="pre">'</span> <span class="pre">']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical_fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">handle_unknown</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'use_encoded_value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">downcast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">NumericTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">na_strings</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">['',</span> <span class="pre">'</span> <span class="pre">']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">categorical_fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'ffill'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">handle_unknown</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'use_encoded_value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">downcast</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>General purpose numeric conversion for pandas dataframes.</p>
 <p>All categorical data and levels must be passed to .fit().
@@ -1453,7 +1461,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.shaping.NumericTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1464,7 +1472,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.shaping.NumericTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1475,7 +1483,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.shaping.NumericTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">convert_dtypes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">convert_dtypes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Convert numeric back to categorical.
 :param df: df
 :type df: pandas.DataFrame
@@ -1485,7 +1493,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.shaping.NumericTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.NumericTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Convert categorical dataset to numeric.</p>
 </dd></dl>
 
@@ -1493,7 +1501,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.clean_weights">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">clean_weights</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">weights</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.clean_weights" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">clean_weights</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">weights</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.clean_weights" title="Link to this definition">¶</a></dt>
 <dd><p>Polish up series weighting information</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1507,7 +1515,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.df_cleanup">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">df_cleanup</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.999</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_data_older_than_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.df_cleanup" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">df_cleanup</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'infer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefill_na</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.999</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_data_older_than_periods</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_most_recent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.df_cleanup" title="Link to this definition">¶</a></dt>
 <dd><p>Pass cleaning functions through to dataframe.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1532,13 +1540,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.freq_to_timedelta">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">freq_to_timedelta</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">freq</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.freq_to_timedelta" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">freq_to_timedelta</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">freq</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.freq_to_timedelta" title="Link to this definition">¶</a></dt>
 <dd><p>Working around pandas limitations.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.infer_frequency">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">infer_frequency</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warn</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.infer_frequency" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">infer_frequency</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df_wide</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warn</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.infer_frequency" title="Link to this definition">¶</a></dt>
 <dd><p>Infer the frequency in a slightly more robust way.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1552,7 +1560,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.long_to_wide">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">long_to_wide</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'datetime'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'series_id'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.long_to_wide" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">long_to_wide</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">date_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'datetime'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">value_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'value'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id_col</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'series_id'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aggfunc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'first'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.long_to_wide" title="Link to this definition">¶</a></dt>
 <dd><p>Take long data and convert into wide, cleaner data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1580,7 +1588,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.simple_train_test_split">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">simple_train_test_split</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.simple_train_test_split" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">simple_train_test_split</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_allowed_train_percent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.simple_train_test_split" title="Link to this definition">¶</a></dt>
 <dd><p>Uses the last periods of forecast_length as the test set, the rest as train</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1602,12 +1610,12 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.split_digits_and_non_digits">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">split_digits_and_non_digits</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">s</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.split_digits_and_non_digits" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">split_digits_and_non_digits</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">s</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.split_digits_and_non_digits" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.subset_series">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">subset_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.subset_series" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">subset_series</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.subset_series" title="Link to this definition">¶</a></dt>
 <dd><p>Return a sample of time series.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1622,7 +1630,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.shaping.wide_to_3d">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">wide_to_3d</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">wide_arr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'gst'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.wide_to_3d" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.shaping.</span></span><span class="sig-name descname"><span class="pre">wide_to_3d</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">wide_arr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonality</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'gst'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.shaping.wide_to_3d" title="Link to this definition">¶</a></dt>
 <dd><p>Generates 3d (groups/seasonality, series, time steps) from wide (time step, series) numpy array.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1639,16 +1647,16 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 </section>
 <section id="module-autots.tools.thresholding">
-<span id="autots-tools-thresholding-module"></span><h2>autots.tools.thresholding module<a class="headerlink" href="#module-autots.tools.thresholding" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-thresholding-module"></span><h2>autots.tools.thresholding module<a class="headerlink" href="#module-autots.tools.thresholding" title="Link to this heading">¶</a></h2>
 <p>Created on Thu Jul  7 10:27:46 2022</p>
 <p>&#64;author: Colin</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.thresholding.NonparametricThreshold">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.thresholding.</span></span><span class="sig-name descname"><span class="pre">NonparametricThreshold</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup_pts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">error_buffer</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">z_init</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">z_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">12.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">z_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_contamination</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sd_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_count_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inverse</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.thresholding.</span></span><span class="sig-name descname"><span class="pre">NonparametricThreshold</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup_pts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">error_buffer</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">z_init</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">z_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">12.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">z_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_contamination</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sd_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">anomaly_count_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inverse</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.thresholding.NonparametricThreshold.compare_to_epsilon">
-<span class="sig-name descname"><span class="pre">compare_to_epsilon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inverse</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold.compare_to_epsilon" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">compare_to_epsilon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inverse</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold.compare_to_epsilon" title="Link to this definition">¶</a></dt>
 <dd><p>Compare smoothed error values to epsilon (error threshold) and group
 consecutive errors together into sequences.</p>
 <dl class="field-list simple">
@@ -1663,7 +1671,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.thresholding.NonparametricThreshold.find_epsilon">
-<span class="sig-name descname"><span class="pre">find_epsilon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inverse</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold.find_epsilon" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">find_epsilon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inverse</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold.find_epsilon" title="Link to this definition">¶</a></dt>
 <dd><p>Find the anomaly threshold that maximizes function representing
 tradeoff between:</p>
 <blockquote>
@@ -1683,7 +1691,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.thresholding.NonparametricThreshold.prune_anoms">
-<span class="sig-name descname"><span class="pre">prune_anoms</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inverse</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold.prune_anoms" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">prune_anoms</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inverse</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold.prune_anoms" title="Link to this definition">¶</a></dt>
 <dd><p>Remove anomalies that don’t meet minimum separation from the next
 closest anomaly or error value</p>
 <dl class="field-list simple">
@@ -1695,7 +1703,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.thresholding.NonparametricThreshold.score_anomalies">
-<span class="sig-name descname"><span class="pre">score_anomalies</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold.score_anomalies" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">score_anomalies</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.NonparametricThreshold.score_anomalies" title="Link to this definition">¶</a></dt>
 <dd><p>Calculate anomaly scores based on max distance from epsilon
 for each anomalous sequence.</p>
 </dd></dl>
@@ -1704,23 +1712,23 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.thresholding.consecutive_groups">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.thresholding.</span></span><span class="sig-name descname"><span class="pre">consecutive_groups</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">iterable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ordering=&lt;function</span> <span class="pre">&lt;lambda&gt;&gt;</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.consecutive_groups" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.thresholding.</span></span><span class="sig-name descname"><span class="pre">consecutive_groups</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">iterable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ordering=&lt;function</span> <span class="pre">&lt;lambda&gt;&gt;</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.consecutive_groups" title="Link to this definition">¶</a></dt>
 <dd><p>Yield groups of consecutive items using <code class="xref py py-func docutils literal notranslate"><span class="pre">itertools.groupby()</span></code>.</p>
 <p>From more_itertools package, see description there for details (circa mid 2022)</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.thresholding.nonparametric">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.thresholding.</span></span><span class="sig-name descname"><span class="pre">nonparametric</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.nonparametric" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.thresholding.</span></span><span class="sig-name descname"><span class="pre">nonparametric</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">series</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.thresholding.nonparametric" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.tools.transform">
-<span id="autots-tools-transform-module"></span><h2>autots.tools.transform module<a class="headerlink" href="#module-autots.tools.transform" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-transform-module"></span><h2>autots.tools.transform module<a class="headerlink" href="#module-autots.tools.transform" title="Link to this heading">¶</a></h2>
 <p>Preprocessing data methods.</p>
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastDiff">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">AlignLastDiff</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">decay_span</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">displacement_rows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">AlignLastDiff</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">quantile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">decay_span</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">displacement_rows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Shift all data relative to the last value(s) of the series.
 This version aligns based on historic diffs rather than direct values.</p>
@@ -1735,7 +1743,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastDiff.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1746,7 +1754,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastDiff.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1757,13 +1765,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastDiff.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastDiff.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">adjustment</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">adjustment</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1777,7 +1785,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastDiff.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastDiff.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1790,7 +1798,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastValue">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">AlignLastValue</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'additive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">strength</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">first_value_only</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">AlignLastValue</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'additive'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">strength</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">first_value_only</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Shift all data relative to the last value(s) of the series.</p>
 <dl class="field-list simple">
@@ -1805,12 +1813,12 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastValue.find_centerpoint">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">find_centerpoint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rows</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lag</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.find_centerpoint" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">find_centerpoint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rows</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lag</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.find_centerpoint" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastValue.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1821,7 +1829,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastValue.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1832,13 +1840,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastValue.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastValue.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">adjustment</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">adjustment</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1852,7 +1860,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AlignLastValue.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AlignLastValue.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1865,11 +1873,11 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.AnomalyRemoval">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">AnomalyRemoval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zscore'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'transformation_params':</span> <span class="pre">{0:</span> <span class="pre">{'datepart_method':</span> <span class="pre">'simple_3',</span> <span class="pre">'regression_model':</span> <span class="pre">{'model':</span> <span class="pre">'ElasticNet',</span> <span class="pre">'model_params':</span> <span class="pre">{}}}},</span> <span class="pre">'transformations':</span> <span class="pre">{0:</span> <span class="pre">'DatepartRegression'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">isolated_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">AnomalyRemoval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zscore'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{'transformation_params':</span> <span class="pre">{0:</span> <span class="pre">{'datepart_method':</span> <span class="pre">'simple_3',</span> <span class="pre">'regression_model':</span> <span class="pre">{'model':</span> <span class="pre">'ElasticNet',</span> <span class="pre">'model_params':</span> <span class="pre">{}}}},</span> <span class="pre">'transformations':</span> <span class="pre">{0:</span> <span class="pre">'DatepartRegression'}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">isolated_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AnomalyRemoval.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.fit" title="Link to this definition">¶</a></dt>
 <dd><p>All will return -1 for anomalies.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1883,13 +1891,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AnomalyRemoval.fit_anomaly_classifier">
-<span class="sig-name descname"><span class="pre">fit_anomaly_classifier</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.fit_anomaly_classifier" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_anomaly_classifier</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.fit_anomaly_classifier" title="Link to this definition">¶</a></dt>
 <dd><p>Fit a model to predict if a score is an anomaly.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AnomalyRemoval.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1900,19 +1908,19 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AnomalyRemoval.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AnomalyRemoval.score_to_anomaly">
-<span class="sig-name descname"><span class="pre">score_to_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scores</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.score_to_anomaly" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">score_to_anomaly</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scores</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.score_to_anomaly" title="Link to this definition">¶</a></dt>
 <dd><p>A DecisionTree model, used as models are nonstandard (and nonparametric).</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.AnomalyRemoval.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.AnomalyRemoval.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1925,7 +1933,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.BKBandpassFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">BKBandpassFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">low</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">K</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lanczos_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_diff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">BKBandpassFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">low</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">K</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lanczos_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_diff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>More complete implentation of Baxter King Bandpass Filter
 based off the successful but somewhat confusing statmodelsfilter transformer.</p>
@@ -1936,7 +1944,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BKBandpassFilter.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1947,7 +1955,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BKBandpassFilter.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1958,13 +1966,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BKBandpassFilter.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BKBandpassFilter.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1975,7 +1983,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BKBandpassFilter.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BKBandpassFilter.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1988,12 +1996,12 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.BTCD">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">BTCD</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'LinearRegression',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BTCD'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">BTCD</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'LinearRegression',</span> <span class="pre">'model_params':</span> <span class="pre">{}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_lags</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BTCD'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Box and Tiao Canonical Decomposition.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BTCD.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2004,7 +2012,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BTCD.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2015,13 +2023,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BTCD.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BTCD.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original space.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2032,7 +2040,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.BTCD.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.BTCD.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2045,7 +2053,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterLastValue">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">CenterLastValue</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">CenterLastValue</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Scale all data relative to the last value(s) of the series.</p>
 <dl class="field-list simple">
@@ -2055,7 +2063,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterLastValue.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2066,7 +2074,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterLastValue.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2077,13 +2085,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterLastValue.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterLastValue.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2094,7 +2102,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterLastValue.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterLastValue.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2107,7 +2115,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterSplit">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">CenterSplit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'zero'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">suffix</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'_mdfcrst'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">CenterSplit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'zero'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">suffix</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'_mdfcrst'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Vaguely Croston inspired approach separating occurrence from magnitude.</p>
 <dl class="field-list simple">
@@ -2120,7 +2128,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterSplit.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2131,7 +2139,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterSplit.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2142,13 +2150,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterSplit.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterSplit.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2159,7 +2167,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CenterSplit.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CenterSplit.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2172,7 +2180,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.ClipOutliers">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">ClipOutliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'clip'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">ClipOutliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'clip'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>PURGE THE OUTLIERS.</p>
 <dl class="field-list simple">
@@ -2186,7 +2194,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ClipOutliers.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2197,7 +2205,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ClipOutliers.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2208,13 +2216,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ClipOutliers.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ClipOutliers.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2225,7 +2233,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ClipOutliers.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ClipOutliers.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2238,12 +2246,12 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.Cointegration">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Cointegration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">det_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_ar_diff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Cointegration'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Cointegration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">det_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_ar_diff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Cointegration'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Johansen Cointegration Decomposition.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Cointegration.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2254,7 +2262,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Cointegration.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2265,13 +2273,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Cointegration.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Cointegration.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original space.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2282,7 +2290,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Cointegration.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Cointegration.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2295,7 +2303,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.CumSumTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">CumSumTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">CumSumTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Cumulative Sum of Data.</p>
 <div class="admonition warning">
@@ -2305,7 +2313,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </div>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CumSumTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2316,7 +2324,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CumSumTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -2324,7 +2332,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CumSumTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns data to original <em>or</em> forecast form</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2340,7 +2348,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.CumSumTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.CumSumTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns changed data
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -2350,18 +2358,18 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.tools.transform.DatepartRegression">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">DatepartRegression</span></span><a class="headerlink" href="#autots.tools.transform.DatepartRegression" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">DatepartRegression</span></span><a class="headerlink" href="#autots.tools.transform.DatepartRegression" title="Link to this definition">¶</a></dt>
 <dd><p>alias of <a class="reference internal" href="#autots.tools.transform.DatepartRegressionTransformer" title="autots.tools.transform.DatepartRegressionTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">DatepartRegressionTransformer</span></code></a></p>
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.DatepartRegressionTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">DatepartRegressionTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'DecisionTree',</span> <span class="pre">'model_params':</span> <span class="pre">{'max_depth':</span> <span class="pre">5,</span> <span class="pre">'min_samples_split':</span> <span class="pre">2}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'expanded'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">DatepartRegressionTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">regression_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'model':</span> <span class="pre">'DecisionTree',</span> <span class="pre">'model_params':</span> <span class="pre">{'max_depth':</span> <span class="pre">5,</span> <span class="pre">'min_samples_split':</span> <span class="pre">2}}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">datepart_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'expanded'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">polynomial_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Remove a regression on datepart from the data. See tools.seasonal.date_part</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DatepartRegressionTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits trend for later detrending.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2372,7 +2380,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DatepartRegressionTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2383,19 +2391,19 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DatepartRegressionTransformer.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_countries_used</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DatepartRegressionTransformer.impute">
-<span class="sig-name descname"><span class="pre">impute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.impute" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">impute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.impute" title="Link to this definition">¶</a></dt>
 <dd><p>Fill Missing. Needs to have same general pattern of missingness (full rows of NaN only or scattered NaN) as was present during .fit()</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DatepartRegressionTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2406,7 +2414,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DatepartRegressionTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DatepartRegressionTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return detrended data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2419,12 +2427,12 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.Detrend">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Detrend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GLS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Detrend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'GLS'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Remove a linear trend from the data.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Detrend.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits trend for later detrending.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2435,7 +2443,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Detrend.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2446,13 +2454,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Detrend.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Detrend.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original form.
 Will only match original if phi==1</p>
 <dl class="field-list simple">
@@ -2464,7 +2472,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Detrend.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Detrend.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return detrended data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2477,11 +2485,11 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.DiffSmoother">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">DiffSmoother</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">adjustment</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reverse_alignment</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">isolated_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">DiffSmoother</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">adjustment</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reverse_alignment</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">isolated_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DiffSmoother.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fit.
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -2489,7 +2497,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DiffSmoother.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns Magical DataFrame
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -2497,13 +2505,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DiffSmoother.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DiffSmoother.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DiffSmoother.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return differenced data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2516,7 +2524,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.DifferencedTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">DifferencedTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">DifferencedTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Difference from lag n value.
 inverse_transform can only be applied to the original series, or an immediately following forecast</p>
@@ -2527,7 +2535,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DifferencedTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fit.
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -2535,7 +2543,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DifferencedTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns Magical DataFrame
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -2543,7 +2551,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DifferencedTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns data to original <em>or</em> forecast form</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2559,7 +2567,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.DifferencedTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.DifferencedTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return differenced data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2572,7 +2580,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.Discretize">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Discretize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">discretization</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Discretize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">discretization</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nan_flag</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Round/convert data to bins.</p>
 <dl class="field-list simple">
@@ -2591,7 +2599,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Discretize.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2602,7 +2610,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Discretize.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2613,13 +2621,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Discretize.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Discretize.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2630,7 +2638,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Discretize.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Discretize.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2643,7 +2651,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.EWMAFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">EWMAFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">span</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EWMAFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">EWMAFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">span</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EWMAFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Irreversible filters of Exponential Weighted Moving Average</p>
 <dl class="field-list simple">
@@ -2653,7 +2661,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.EWMAFilter.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EWMAFilter.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EWMAFilter.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2664,13 +2672,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.EWMAFilter.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EWMAFilter.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EWMAFilter.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.EWMAFilter.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EWMAFilter.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EWMAFilter.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return detrended data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2683,12 +2691,12 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.EmptyTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">EmptyTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'EmptyTransformer'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">EmptyTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'EmptyTransformer'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Base transformer returning raw data.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.EmptyTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2699,7 +2707,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.EmptyTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2710,13 +2718,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.EmptyTransformer.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.EmptyTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2727,7 +2735,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.EmptyTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.EmptyTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2740,7 +2748,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTDecomposition">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">FFTDecomposition</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_harmonics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detrend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">FFTDecomposition</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_harmonics</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detrend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>FFT decomposition, then removal, then extrapolation and addition.</p>
 <dl class="field-list simple">
@@ -2753,7 +2761,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTDecomposition.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2764,7 +2772,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTDecomposition.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2775,13 +2783,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTDecomposition.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTDecomposition.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2792,7 +2800,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTDecomposition.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTDecomposition.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2805,7 +2813,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">FFTFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reverse</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">FFTFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reverse</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Fit Fourier Transform and keep only lowest frequencies below cutoff</p>
 <dl class="field-list simple">
@@ -2818,7 +2826,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTFilter.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2829,7 +2837,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTFilter.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2840,13 +2848,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTFilter.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTFilter.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2857,7 +2865,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FFTFilter.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FFTFilter.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2870,7 +2878,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.FastICA">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">FastICA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">FastICA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>sklearn FastICA for signal decomposition. But need to store columns.</p>
 <dl class="field-list simple">
@@ -2880,7 +2888,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FastICA.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2891,7 +2899,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FastICA.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2902,13 +2910,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FastICA.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FastICA.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2919,7 +2927,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.FastICA.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.FastICA.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2932,7 +2940,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.GeneralTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">GeneralTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reconciliation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">GeneralTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformation_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reconciliation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>Remove fillNA and then mathematical transformations.</p>
 <p>Expects a chronologically sorted pandas.DataFrame with a DatetimeIndex, only numeric data, and a ‘wide’ (one column per series) shape.</p>
@@ -3037,7 +3045,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.GeneralTransformer.fill_na">
-<span class="sig-name descname"><span class="pre">fill_na</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.fill_na" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fill_na</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.fill_na" title="Link to this definition">¶</a></dt>
 <dd><dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
@@ -3053,7 +3061,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.GeneralTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Apply transformations and return transformer object.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3064,18 +3072,18 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.GeneralTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Directly fit and apply transformations to convert df.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.GeneralTransformer.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'fast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.get_new_params" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.GeneralTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillzero</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillzero</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Undo the madness.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3091,7 +3099,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.GeneralTransformer.retrieve_transformer">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">retrieve_transformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.retrieve_transformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">retrieve_transformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2020</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.retrieve_transformer" title="Link to this definition">¶</a></dt>
 <dd><p>Retrieves a specific transformer object from a string.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3109,7 +3117,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.GeneralTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.GeneralTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Apply transformations to convert df.</p>
 </dd></dl>
 
@@ -3117,7 +3125,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.HPFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">HPFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'trend'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lamb</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1600</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HPFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">HPFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'trend'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lamb</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1600</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HPFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Irreversible filters.</p>
 <dl class="field-list simple">
@@ -3127,7 +3135,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HPFilter.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HPFilter.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HPFilter.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3138,13 +3146,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HPFilter.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HPFilter.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HPFilter.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HPFilter.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HPFilter.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HPFilter.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return detrended data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3157,7 +3165,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.HistoricValues">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">HistoricValues</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">HistoricValues</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Overwrite (align) all forecast values with the nearest actual value in window (tail) of history.
 (affected by upstream transformers, as usual)</p>
@@ -3168,7 +3176,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HistoricValues.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3179,7 +3187,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HistoricValues.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3190,13 +3198,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HistoricValues.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HistoricValues.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3207,7 +3215,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HistoricValues.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HistoricValues.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3220,11 +3228,11 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.HolidayTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">HolidayTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_occurrences</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">splash_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.65</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dayofmonth_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_excess_anomalies</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">impact</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">HolidayTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">anomaly_detector_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_occurrences</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">splash_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.65</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dayofmonth_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_wkdeom_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_lunar_weekday</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_islamic_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_hebrew_holidays</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_excess_anomalies</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">impact</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'multivariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HolidayTransformer.dates_to_holidays">
-<span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">style</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_features</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">365</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.dates_to_holidays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">dates_to_holidays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dates</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">style</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'flag'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_impacts</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_features</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">365</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.dates_to_holidays" title="Link to this definition">¶</a></dt>
 <dd><p>dates (pd.DatetimeIndex): list of dates
 style (str): option for how to return information</p>
 <blockquote>
@@ -3238,13 +3246,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HolidayTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Run holiday detection. Input wide-style pandas time series.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HolidayTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3255,13 +3263,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HolidayTransformer.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HolidayTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3272,7 +3280,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.HolidayTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.HolidayTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3285,7 +3293,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.IntermittentOccurrence">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">IntermittentOccurrence</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'median'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">IntermittentOccurrence</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'median'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Intermittent inspired binning predicts probability of not center.</p>
 <p>Does not inverse to original values!</p>
@@ -3296,7 +3304,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.IntermittentOccurrence.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits shift interval.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3307,7 +3315,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.IntermittentOccurrence.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3318,13 +3326,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.IntermittentOccurrence.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.IntermittentOccurrence.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3335,7 +3343,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.IntermittentOccurrence.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.IntermittentOccurrence.transform" title="Link to this definition">¶</a></dt>
 <dd><p>0 if Median. 1 if &gt; Median, -1 if less.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3348,7 +3356,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.KalmanSmoothing">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">KalmanSmoothing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">state_transition</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[1,</span> <span class="pre">1],</span> <span class="pre">[0,</span> <span class="pre">1]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[0.1,</span> <span class="pre">0.0],</span> <span class="pre">[0.0,</span> <span class="pre">0.01]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[1,</span> <span class="pre">0]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">em_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">KalmanSmoothing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">state_transition</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[1,</span> <span class="pre">1],</span> <span class="pre">[0,</span> <span class="pre">1]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[0.1,</span> <span class="pre">0.0],</span> <span class="pre">[0.0,</span> <span class="pre">0.01]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[[1,</span> <span class="pre">0]]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observation_noise</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">em_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Apply a Kalman Filter to smooth data given a transition matrix.</p>
 <dl class="field-list simple">
@@ -3363,7 +3371,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.KalmanSmoothing.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3374,7 +3382,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.KalmanSmoothing.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3385,13 +3393,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.KalmanSmoothing.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.KalmanSmoothing.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3402,7 +3410,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.KalmanSmoothing.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.KalmanSmoothing.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3415,7 +3423,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.LevelShiftMagic">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">LevelShiftMagic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">90</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_forward_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_level_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alignment</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'average'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">LevelShiftMagic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">90</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grouping_forward_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_level_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alignment</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'average'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Detects and corrects for level shifts. May seriously alter trend.</p>
 <dl class="field-list simple">
@@ -3429,7 +3437,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LevelShiftMagic.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3440,7 +3448,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LevelShiftMagic.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3451,13 +3459,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LevelShiftMagic.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LevelShiftMagic.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3468,7 +3476,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LevelShiftMagic.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LevelShiftMagic.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3481,13 +3489,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="autots.tools.transform.LevelShiftTransformer">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">LevelShiftTransformer</span></span><a class="headerlink" href="#autots.tools.transform.LevelShiftTransformer" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">LevelShiftTransformer</span></span><a class="headerlink" href="#autots.tools.transform.LevelShiftTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>alias of <a class="reference internal" href="#autots.tools.transform.LevelShiftMagic" title="autots.tools.transform.LevelShiftMagic"><code class="xref py py-class docutils literal notranslate"><span class="pre">LevelShiftMagic</span></code></a></p>
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.LocalLinearTrend">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">LocalLinearTrend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rolling_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_future</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macro_micro</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">suffix</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'_lltmicro'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">LocalLinearTrend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rolling_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_future</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">macro_micro</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">suffix</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'_lltmicro'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Remove a rolling linear trend.
 Note this will probably perform poorly with long forecast horizons as forecast trend is simply the tail (n_future) of data’s trend.</p>
@@ -3502,7 +3510,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LocalLinearTrend.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3513,7 +3521,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LocalLinearTrend.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3524,13 +3532,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LocalLinearTrend.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LocalLinearTrend.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3541,7 +3549,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.LocalLinearTrend.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.LocalLinearTrend.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3554,7 +3562,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.MeanDifference">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">MeanDifference</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">MeanDifference</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Difference from lag n value, but differenced by mean of all series.
 inverse_transform can only be applied to the original series, or an immediately following forecast</p>
@@ -3565,7 +3573,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.MeanDifference.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fit.
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -3573,7 +3581,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.MeanDifference.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns Magical DataFrame
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -3581,7 +3589,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.MeanDifference.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns data to original <em>or</em> forecast form</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3597,7 +3605,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.MeanDifference.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.MeanDifference.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return differenced data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3610,7 +3618,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.PCA">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">PCA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">PCA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>sklearn PCA for signal decomposition. But need to store columns.</p>
 <dl class="field-list simple">
@@ -3620,7 +3628,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PCA.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3631,7 +3639,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PCA.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3642,13 +3650,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PCA.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PCA.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3659,7 +3667,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PCA.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PCA.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3672,7 +3680,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.PctChangeTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">PctChangeTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">PctChangeTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>% Change of Data.</p>
 <div class="admonition warning">
@@ -3683,7 +3691,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </div>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PctChangeTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3694,7 +3702,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PctChangeTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return <em>Magical</em> DataFrame.
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -3702,7 +3710,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PctChangeTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns data to original <em>or</em> forecast form</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3718,7 +3726,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PctChangeTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PctChangeTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns changed data
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -3728,7 +3736,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.PositiveShift">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">PositiveShift</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">log</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center_one</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squared</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">PositiveShift</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">log</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center_one</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squared</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Shift each series if necessary to assure all values &gt;= 1.</p>
 <dl class="field-list simple">
@@ -3742,7 +3750,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PositiveShift.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits shift interval.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3753,7 +3761,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PositiveShift.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3764,7 +3772,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PositiveShift.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3775,7 +3783,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.PositiveShift.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.PositiveShift.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return detrended data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3788,19 +3796,19 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.RandomTransform">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">RandomTransform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{None:</span> <span class="pre">0.0,</span> <span class="pre">'MinMaxScaler':</span> <span class="pre">0.03,</span> <span class="pre">'PowerTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'QuantileTransformer':</span> <span class="pre">0.03,</span> <span class="pre">'MaxAbsScaler':</span> <span class="pre">0.03,</span> <span class="pre">'StandardScaler':</span> <span class="pre">0.04,</span> <span class="pre">'RobustScaler':</span> <span class="pre">0.03,</span> <span class="pre">'PCA':</span> <span class="pre">0.01,</span> <span class="pre">'FastICA':</span> <span class="pre">0.01,</span> <span class="pre">'Detrend':</span> <span class="pre">0.02,</span> <span class="pre">'RollingMeanTransformer':</span> <span class="pre">0.02,</span> <span class="pre">'RollingMean100thN':</span> <span class="pre">0.01,</span> <span class="pre">'DifferencedTransformer':</span> <span class="pre">0.05,</span> <span class="pre">'SinTrend':</span> <span class="pre">0.01,</span> <span class="pre">'PctChangeTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'CumSumTransformer':</span> <span class="pre">0.02,</span> <span class="pre">'PositiveShift':</span> <span class="pre">0.02,</span> <span class="pre">'Log':</span> <span class="pre">0.01,</span> <span class="pre">'IntermittentOccurrence':</span> <span class="pre">0.01,</span> <span class="pre">'SeasonalDifference':</span> <span class="pre">0.06,</span> <span class="pre">'cffilter':</span> <span class="pre">0.01,</span> <span class="pre">'bkfilter':</span> <span class="pre">0.05,</span> <span class="pre">'convolution_filter':</span> <span class="pre">0.001,</span> <span class="pre">'HPFilter':</span> <span class="pre">0.01,</span> <span class="pre">'DatepartRegression':</span> <span class="pre">0.01,</span> <span class="pre">'ClipOutliers':</span> <span class="pre">0.03,</span> <span class="pre">'Discretize':</span> <span class="pre">0.01,</span> <span class="pre">'CenterLastValue':</span> <span class="pre">0.01,</span> <span class="pre">'Round':</span> <span class="pre">0.02,</span> <span class="pre">'Slice':</span> <span class="pre">0.02,</span> <span class="pre">'ScipyFilter':</span> <span class="pre">0.02,</span> <span class="pre">'STLFilter':</span> <span class="pre">0.01,</span> <span class="pre">'EWMAFilter':</span> <span class="pre">0.02,</span> <span class="pre">'MeanDifference':</span> <span class="pre">0.002,</span> <span class="pre">'BTCD':</span> <span class="pre">0.01,</span> <span class="pre">'Cointegration':</span> <span class="pre">0.01,</span> <span class="pre">'AlignLastValue':</span> <span class="pre">0.2,</span> <span class="pre">'AnomalyRemoval':</span> <span class="pre">0.03,</span> <span class="pre">'HolidayTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'LocalLinearTrend':</span> <span class="pre">0.01,</span> <span class="pre">'KalmanSmoothing':</span> <span class="pre">0.02,</span> <span class="pre">'RegressionFilter':</span> <span class="pre">0.02,</span> <span class="pre">'LevelShiftTransformer':</span> <span class="pre">0.03,</span> <span class="pre">'CenterSplit':</span> <span class="pre">0.01,</span> <span class="pre">'FFTFilter':</span> <span class="pre">0.01,</span> <span class="pre">'FFTDecomposition':</span> <span class="pre">0.01,</span> <span class="pre">'ReplaceConstant':</span> <span class="pre">0.02,</span> <span class="pre">'AlignLastDiff':</span> <span class="pre">0.01,</span> <span class="pre">'DiffSmoother':</span> <span class="pre">0.005,</span> <span class="pre">'HistoricValues':</span> <span class="pre">0.01,</span> <span class="pre">'BKBandpassFilter':</span> <span class="pre">0.01}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_prob_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'ffill':</span> <span class="pre">0.4,</span> <span class="pre">'fake_date':</span> <span class="pre">0.1,</span> <span class="pre">'rolling_mean':</span> <span class="pre">0.1,</span> <span class="pre">'rolling_mean_24':</span> <span class="pre">0.1,</span> <span class="pre">'IterativeImputer':</span> <span class="pre">0.025,</span> <span class="pre">'mean':</span> <span class="pre">0.06,</span> <span class="pre">'zero':</span> <span class="pre">0.05,</span> <span class="pre">'ffill_mean_biased':</span> <span class="pre">0.1,</span> <span class="pre">'median':</span> <span class="pre">0.03,</span> <span class="pre">None:</span> <span class="pre">0.001,</span> <span class="pre">'interpolate':</span> <span class="pre">0.4,</span> <span class="pre">'KNNImputer':</span> <span class="pre">0.05,</span> <span class="pre">'IterativeImputerExtraTrees':</span> <span class="pre">0.0001,</span> <span class="pre">'SeasonalityMotifImputer':</span> <span class="pre">0.1,</span> <span class="pre">'SeasonalityMotifImputerLinMix':</span> <span class="pre">0.01,</span> <span class="pre">'SeasonalityMotifImputer1K':</span> <span class="pre">0.01,</span> <span class="pre">'DatepartRegressionImputer':</span> <span class="pre">0.05}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fast_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">superfast_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">traditional_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_min_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_none</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_nan_fill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RandomTransform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">RandomTransform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'AlignLastDiff':</span> <span class="pre">0.01,</span> <span class="pre">'AlignLastValue':</span> <span class="pre">0.2,</span> <span class="pre">'AnomalyRemoval':</span> <span class="pre">0.03,</span> <span class="pre">'BKBandpassFilter':</span> <span class="pre">0.01,</span> <span class="pre">'BTCD':</span> <span class="pre">0.01,</span> <span class="pre">'CenterLastValue':</span> <span class="pre">0.01,</span> <span class="pre">'CenterSplit':</span> <span class="pre">0.01,</span> <span class="pre">'ClipOutliers':</span> <span class="pre">0.03,</span> <span class="pre">'Cointegration':</span> <span class="pre">0.01,</span> <span class="pre">'CumSumTransformer':</span> <span class="pre">0.02,</span> <span class="pre">'DatepartRegression':</span> <span class="pre">0.01,</span> <span class="pre">'Detrend':</span> <span class="pre">0.02,</span> <span class="pre">'DiffSmoother':</span> <span class="pre">0.005,</span> <span class="pre">'DifferencedTransformer':</span> <span class="pre">0.05,</span> <span class="pre">'Discretize':</span> <span class="pre">0.01,</span> <span class="pre">'EWMAFilter':</span> <span class="pre">0.02,</span> <span class="pre">'FFTDecomposition':</span> <span class="pre">0.01,</span> <span class="pre">'FFTFilter':</span> <span class="pre">0.01,</span> <span class="pre">'FastICA':</span> <span class="pre">0.01,</span> <span class="pre">'HPFilter':</span> <span class="pre">0.01,</span> <span class="pre">'HistoricValues':</span> <span class="pre">0.01,</span> <span class="pre">'HolidayTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'IntermittentOccurrence':</span> <span class="pre">0.01,</span> <span class="pre">'KalmanSmoothing':</span> <span class="pre">0.02,</span> <span class="pre">'LevelShiftTransformer':</span> <span class="pre">0.03,</span> <span class="pre">'LocalLinearTrend':</span> <span class="pre">0.01,</span> <span class="pre">'Log':</span> <span class="pre">0.01,</span> <span class="pre">'MaxAbsScaler':</span> <span class="pre">0.03,</span> <span class="pre">'MeanDifference':</span> <span class="pre">0.002,</span> <span class="pre">'MinMaxScaler':</span> <span class="pre">0.03,</span> <span class="pre">'PCA':</span> <span class="pre">0.01,</span> <span class="pre">'PctChangeTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'PositiveShift':</span> <span class="pre">0.02,</span> <span class="pre">'PowerTransformer':</span> <span class="pre">0.01,</span> <span class="pre">'QuantileTransformer':</span> <span class="pre">0.03,</span> <span class="pre">'RegressionFilter':</span> <span class="pre">0.02,</span> <span class="pre">'ReplaceConstant':</span> <span class="pre">0.02,</span> <span class="pre">'RobustScaler':</span> <span class="pre">0.03,</span> <span class="pre">'RollingMean100thN':</span> <span class="pre">0.01,</span> <span class="pre">'RollingMeanTransformer':</span> <span class="pre">0.02,</span> <span class="pre">'Round':</span> <span class="pre">0.02,</span> <span class="pre">'STLFilter':</span> <span class="pre">0.01,</span> <span class="pre">'ScipyFilter':</span> <span class="pre">0.02,</span> <span class="pre">'SeasonalDifference':</span> <span class="pre">0.06,</span> <span class="pre">'SinTrend':</span> <span class="pre">0.01,</span> <span class="pre">'Slice':</span> <span class="pre">0.02,</span> <span class="pre">'StandardScaler':</span> <span class="pre">0.04,</span> <span class="pre">'bkfilter':</span> <span class="pre">0.05,</span> <span class="pre">'cffilter':</span> <span class="pre">0.01,</span> <span class="pre">'convolution_filter':</span> <span class="pre">0.001,</span> <span class="pre">None:</span> <span class="pre">0.0}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_max_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">na_prob_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">{'DatepartRegressionImputer':</span> <span class="pre">0.05,</span> <span class="pre">'IterativeImputer':</span> <span class="pre">0.025,</span> <span class="pre">'IterativeImputerExtraTrees':</span> <span class="pre">0.0001,</span> <span class="pre">'KNNImputer':</span> <span class="pre">0.05,</span> <span class="pre">'SeasonalityMotifImputer':</span> <span class="pre">0.1,</span> <span class="pre">'SeasonalityMotifImputer1K':</span> <span class="pre">0.01,</span> <span class="pre">'SeasonalityMotifImputerLinMix':</span> <span class="pre">0.01,</span> <span class="pre">'fake_date':</span> <span class="pre">0.1,</span> <span class="pre">'ffill':</span> <span class="pre">0.4,</span> <span class="pre">'ffill_mean_biased':</span> <span class="pre">0.1,</span> <span class="pre">'interpolate':</span> <span class="pre">0.4,</span> <span class="pre">'mean':</span> <span class="pre">0.06,</span> <span class="pre">'median':</span> <span class="pre">0.03,</span> <span class="pre">'rolling_mean':</span> <span class="pre">0.1,</span> <span class="pre">'rolling_mean_24':</span> <span class="pre">0.1,</span> <span class="pre">'zero':</span> <span class="pre">0.05,</span> <span class="pre">None:</span> <span class="pre">0.001}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fast_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">superfast_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">traditional_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transformer_min_depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_none</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">no_nan_fill</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RandomTransform" title="Link to this definition">¶</a></dt>
 <dd><p>Return a dict of randomly choosen transformation selections.</p>
 <p>BTCD is used as a signal that slow parameters are allowed.</p>
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.RegressionFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">RegressionFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'RegressionFilter'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">90</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">run_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'season_first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">RegressionFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'RegressionFilter'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rolling_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">90</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">run_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'season_first'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">holiday_country</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'US'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Models seasonal and local linear trend, and clips std dvs from this fit.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RegressionFilter.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3811,7 +3819,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RegressionFilter.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3822,13 +3830,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RegressionFilter.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RegressionFilter.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>No changes made.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3839,7 +3847,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RegressionFilter.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RegressionFilter.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3852,7 +3860,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.ReplaceConstant">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">ReplaceConstant</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">constant</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reintroduction_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">ReplaceConstant</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">constant</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fillna</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'linear'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reintroduction_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Replace constant, filling the NaN, then possibly reintroducing.
 If reintroducion is used, it is unlikely inverse_transform will match original exactly.</p>
@@ -3867,7 +3875,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ReplaceConstant.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3878,7 +3886,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ReplaceConstant.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3889,13 +3897,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ReplaceConstant.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ReplaceConstant.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3906,7 +3914,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ReplaceConstant.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ReplaceConstant.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3919,7 +3927,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.RollingMeanTransformer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">RollingMeanTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fixed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">RollingMeanTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fixed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Attempt at Rolling Mean with built-in inverse_transform for time series
 inverse_transform can only be applied to the original series, or an immediately following forecast
@@ -3932,7 +3940,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RollingMeanTransformer.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3943,7 +3951,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RollingMeanTransformer.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns Magical DataFrame
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -3951,13 +3959,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RollingMeanTransformer.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RollingMeanTransformer.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns data to original <em>or</em> forecast form</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3973,7 +3981,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.RollingMeanTransformer.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.RollingMeanTransformer.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns rolling data
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -3983,7 +3991,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.Round">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Round</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">decimals</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">on_transform</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">on_inverse</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_int</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Round</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">decimals</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">on_transform</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">on_inverse</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_int</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Round all values. Convert into Integers if decimal &lt;= 0.</p>
 <p>Inverse_transform will not undo the transformation!</p>
@@ -3999,7 +4007,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Round.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4010,7 +4018,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Round.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4021,13 +4029,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Round.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Round.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4038,7 +4046,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Round.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Round.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4051,7 +4059,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.STLFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">STLFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">decomp_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'STL'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'trend'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.STLFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">STLFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">decomp_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'STL'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">part</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'trend'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seasonal</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.STLFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Irreversible filters.</p>
 <dl class="field-list simple">
@@ -4065,7 +4073,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.STLFilter.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.STLFilter.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.STLFilter.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4076,13 +4084,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.STLFilter.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.STLFilter.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.STLFilter.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.STLFilter.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.STLFilter.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.STLFilter.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return detrended data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4095,7 +4103,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.ScipyFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">ScipyFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hilbert'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">ScipyFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hilbert'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method_args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Irreversible filters from Scipy</p>
 <dl class="field-list simple">
@@ -4108,7 +4116,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ScipyFilter.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits filter.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4119,7 +4127,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ScipyFilter.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4130,13 +4138,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ScipyFilter.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ScipyFilter.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4147,7 +4155,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.ScipyFilter.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.ScipyFilter.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return detrended data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4160,7 +4168,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.SeasonalDifference">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">SeasonalDifference</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lag_1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'LastValue'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">SeasonalDifference</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lag_1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'LastValue'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Remove seasonal component.</p>
 <p>“Oh that’s nice - ash on my tomatoes!” - Pippin</p>
@@ -4174,7 +4182,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SeasonalDifference.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4185,7 +4193,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SeasonalDifference.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns Magical DataFrame
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -4193,13 +4201,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SeasonalDifference.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SeasonalDifference.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns data to original <em>or</em> forecast form</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4215,7 +4223,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SeasonalDifference.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SeasonalDifference.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns rolling data
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -4225,12 +4233,12 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.SinTrend">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">SinTrend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'lm'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">SinTrend</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'lm'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Modelling sin.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SinTrend.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Fits trend for later detrending
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -4238,14 +4246,14 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SinTrend.fit_sin">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">fit_sin</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">tt</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">yy</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'lm'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.fit_sin" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">fit_sin</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">tt</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">yy</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'lm'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.fit_sin" title="Link to this definition">¶</a></dt>
 <dd><p>Fit sin to the input time sequence, and return fitting parameters “amp”, “omega”, “phase”, “offset”, “freq”, “period” and “fitfunc”</p>
 <p>from user unsym &#64; <a class="reference external" href="https://stackoverflow.com/questions/16716302/how-do-i-fit-a-sine-curve-to-my-data-with-pylab-and-numpy">https://stackoverflow.com/questions/16716302/how-do-i-fit-a-sine-curve-to-my-data-with-pylab-and-numpy</a></p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SinTrend.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns Detrended DataFrame
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -4253,13 +4261,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SinTrend.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SinTrend.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns data to original form
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -4267,7 +4275,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.SinTrend.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.SinTrend.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Returns detrended data
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -4277,7 +4285,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.Slice">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Slice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'100'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">Slice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'100'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Take the .tail() of the data returning only most recent values.</p>
 <p>Inverse_transform will not undo the transformation!</p>
@@ -4291,7 +4299,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Slice.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.fit" title="Link to this definition">¶</a></dt>
 <dd><p>Learn behavior of data to change.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4302,7 +4310,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Slice.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fits and Returns <em>Magical</em> DataFrame.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4313,13 +4321,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Slice.get_new_params">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.get_new_params" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_new_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'random'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.get_new_params" title="Link to this definition">¶</a></dt>
 <dd><p>Generate new random parameters</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Slice.inverse_transform">
-<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.inverse_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inverse_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trans_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.inverse_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return data to original <em>or</em> forecast form.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4330,7 +4338,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.Slice.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.Slice.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return changed data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4343,29 +4351,29 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py class">
 <dt class="sig sig-object py" id="autots.tools.transform.StatsmodelsFilter">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">StatsmodelsFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bkfilter'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">StatsmodelsFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'bkfilter'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#autots.tools.transform.EmptyTransformer" title="autots.tools.transform.EmptyTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">EmptyTransformer</span></code></a></p>
 <p>Irreversible filters.
 :param method: bkfilter or cffilter or convolution_filter
 :type method: str</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.StatsmodelsFilter.bkfilter">
-<span class="sig-name descname"><span class="pre">bkfilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.bkfilter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">bkfilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.bkfilter" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.StatsmodelsFilter.cffilter">
-<span class="sig-name descname"><span class="pre">cffilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.cffilter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">cffilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.cffilter" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.StatsmodelsFilter.convolution_filter">
-<span class="sig-name descname"><span class="pre">convolution_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.convolution_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">convolution_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.convolution_filter" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.StatsmodelsFilter.fit_transform">
-<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.fit_transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.fit_transform" title="Link to this definition">¶</a></dt>
 <dd><p>Fit and Return Detrended DataFrame.
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -4373,7 +4381,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py method">
 <dt class="sig sig-object py" id="autots.tools.transform.StatsmodelsFilter.transform">
-<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.transform" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.StatsmodelsFilter.transform" title="Link to this definition">¶</a></dt>
 <dd><p>Return detrended data.
 :param df: input dataframe
 :type df: pandas.DataFrame</p>
@@ -4383,13 +4391,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.bkfilter_st">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">bkfilter_st</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">low</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">K</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">12</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lanczos_factor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.bkfilter_st" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">bkfilter_st</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">low</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">K</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">12</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lanczos_factor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.bkfilter_st" title="Link to this definition">¶</a></dt>
 <dd><p>This code is mostly from Statsmodel’s bkfilter function.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.clip_outliers">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">clip_outliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.clip_outliers" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">clip_outliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.clip_outliers" title="Link to this definition">¶</a></dt>
 <dd><p>Replace outliers above threshold with that threshold. Axis = 0.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4403,24 +4411,24 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.exponential_decay">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">exponential_decay</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">span</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">halflife</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.exponential_decay" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">exponential_decay</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">span</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">halflife</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.exponential_decay" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.get_transformer_params">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">get_transformer_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'EmptyTransformer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.get_transformer_params" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">get_transformer_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'EmptyTransformer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.get_transformer_params" title="Link to this definition">¶</a></dt>
 <dd><p>Retrieve new random params for new Transformers.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.random_cleaners">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">random_cleaners</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.random_cleaners" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">random_cleaners</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.random_cleaners" title="Link to this definition">¶</a></dt>
 <dd><p>Returns transformation params that clean data without shifting.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.remove_outliers">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">remove_outliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.remove_outliers" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">remove_outliers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.remove_outliers" title="Link to this definition">¶</a></dt>
 <dd><p>Replace outliers with np.nan.
 <a class="reference external" href="https://stackoverflow.com/questions/23199796/detect-and-exclude-outliers-in-pandas-data-frame">https://stackoverflow.com/questions/23199796/detect-and-exclude-outliers-in-pandas-data-frame</a></p>
 <dl class="field-list simple">
@@ -4435,7 +4443,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.simple_context_slicer">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">simple_context_slicer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'None'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.simple_context_slicer" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">simple_context_slicer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'None'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.simple_context_slicer" title="Link to this definition">¶</a></dt>
 <dd><p>Condensed version of context_slicer with more limited options.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4460,16 +4468,16 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.transform.transformer_list_to_dict">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">transformer_list_to_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.transformer_list_to_dict" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.transform.</span></span><span class="sig-name descname"><span class="pre">transformer_list_to_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformer_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.transform.transformer_list_to_dict" title="Link to this definition">¶</a></dt>
 <dd><p>Convert various possibilities to dict.</p>
 </dd></dl>
 
 </section>
 <section id="module-autots.tools.window_functions">
-<span id="autots-tools-window-functions-module"></span><h2>autots.tools.window_functions module<a class="headerlink" href="#module-autots.tools.window_functions" title="Permalink to this heading">¶</a></h2>
+<span id="autots-tools-window-functions-module"></span><h2>autots.tools.window_functions module<a class="headerlink" href="#module-autots.tools.window_functions" title="Link to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.chunk_reshape">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">chunk_reshape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size=10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunk_size=100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sample_fraction=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed=7734</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.float32'&gt;</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.chunk_reshape" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">chunk_reshape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size=10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunk_size=100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sample_fraction=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed=7734</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.float32'&gt;</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.chunk_reshape" title="Link to this definition">¶</a></dt>
 <dd><p>Shifts from (n_records, n_series) to (windows, window_size).
 Multivariate.
 More memory efficient, if not quite as fast as x.reshape(-1, x.shape[-1]) for 3D numpy array.</p>
@@ -4477,18 +4485,18 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.last_window">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">last_window</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'univariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.last_window" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">last_window</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'univariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.last_window" title="Link to this definition">¶</a></dt>
 <dd><p>Pandas based function to provide the last window of window_maker.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.np_2d_arange">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">np_2d_arange</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">start</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stop</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.np_2d_arange" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">np_2d_arange</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">start</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stop</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.np_2d_arange" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.retrieve_closest_indices">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">retrieve_closest_indices</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_indices</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'braycurtis'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_differenced</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_last</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.retrieve_closest_indices" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">retrieve_closest_indices</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_indices</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_metric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'braycurtis'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_differenced</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_last</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.retrieve_closest_indices" title="Link to this definition">¶</a></dt>
 <dd><p>Find next indicies closest to the final segment of forecast_length</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4508,7 +4516,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.rolling_window_view">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">rolling_window_view</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(0,)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">writeable</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.rolling_window_view" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">rolling_window_view</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(0,)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">writeable</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.rolling_window_view" title="Link to this definition">¶</a></dt>
 <dd><p>Create a view of <cite>array</cite> which for every point gives the n-dimensional
 neighbourhood of size window. New dimensions are added at the end of
 <cite>array</cite> or after the corresponding original dimension.</p>
@@ -4534,13 +4542,13 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.sliding_window_view">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">sliding_window_view</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(0,)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">writeable</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.sliding_window_view" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">sliding_window_view</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(0,)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">writeable</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.sliding_window_view" title="Link to this definition">¶</a></dt>
 <dd><p>Toggles between numpy and internal version depending on np.__version__.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_id_maker">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_id_maker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_id_maker" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_id_maker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_id_maker" title="Link to this definition">¶</a></dt>
 <dd><p>Create indices for array of multiple window slices of data</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4560,25 +4568,25 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_lin_reg">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_lin_reg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_lin_reg" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_lin_reg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_lin_reg" title="Link to this definition">¶</a></dt>
 <dd><p>From <a class="reference external" href="https://stackoverflow.com/questions/70296498/efficient-computation-of-moving-linear-regression-with-numpy-numba/70304475#70304475">https://stackoverflow.com/questions/70296498/efficient-computation-of-moving-linear-regression-with-numpy-numba/70304475#70304475</a></p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_lin_reg_mean">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_lin_reg_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_lin_reg_mean" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_lin_reg_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_lin_reg_mean" title="Link to this definition">¶</a></dt>
 <dd><p>From <a class="reference external" href="https://stackoverflow.com/questions/70296498/efficient-computation-of-moving-linear-regression-with-numpy-numba/70304475#70304475">https://stackoverflow.com/questions/70296498/efficient-computation-of-moving-linear-regression-with-numpy-numba/70304475#70304475</a></p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_lin_reg_mean_no_nan">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_lin_reg_mean_no_nan</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_lin_reg_mean_no_nan" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_lin_reg_mean_no_nan</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_lin_reg_mean_no_nan" title="Link to this definition">¶</a></dt>
 <dd><p>From <a class="reference external" href="https://stackoverflow.com/questions/70296498/efficient-computation-of-moving-linear-regression-with-numpy-numba/70304475#70304475">https://stackoverflow.com/questions/70296498/efficient-computation-of-moving-linear-regression-with-numpy-numba/70304475#70304475</a></p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_maker">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_maker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'univariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast_length'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1234</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_maker" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_maker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'univariate'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalize_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_dim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'forecast_length'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forecast_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_windows</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">regression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">future_regressor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1234</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_maker" title="Link to this definition">¶</a></dt>
 <dd><p>Convert a dataset into slices with history and y forecast.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -4603,7 +4611,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_maker_2">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_maker_2</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_maker_2" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_maker_2</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start_index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_maker_2" title="Link to this definition">¶</a></dt>
 <dd><p>Create array of multiple window slices of data
 Note that this returns a different orientation than window_maker_3</p>
 <dl class="field-list simple">
@@ -4625,7 +4633,7 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_maker_3">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_maker_3</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_maker_3" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_maker_3</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_maker_3" title="Link to this definition">¶</a></dt>
 <dd><p>stride tricks version of window. About 40% faster than window_maker_2
 Note that this returns a different orientation than window_maker_2</p>
 <dl class="field-list simple">
@@ -4644,22 +4652,22 @@ <h3>Usage example<a class="headerlink" href="#usage-example" title="Permalink to
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_sum_mean">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_sum_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_sum_mean" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_sum_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_sum_mean" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_sum_mean_nan_tail">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_sum_mean_nan_tail</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_sum_mean_nan_tail" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_sum_mean_nan_tail</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_sum_mean_nan_tail" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="autots.tools.window_functions.window_sum_nan_mean">
-<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_sum_nan_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_sum_nan_mean" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">autots.tools.window_functions.</span></span><span class="sig-name descname"><span class="pre">window_sum_nan_mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#autots.tools.window_functions.window_sum_nan_mean" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-autots.tools">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.tools" title="Permalink to this heading">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-autots.tools" title="Link to this heading">¶</a></h2>
 <p>Basic utilities.</p>
 </section>
 </section>
@@ -4753,21 +4761,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/source/intro.html b/docs/build/html/source/intro.html
index 477637e4..18861acc 100644
--- a/docs/build/html/source/intro.html
+++ b/docs/build/html/source/intro.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="../">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>Intro &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
-    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/doctools.js"></script>
-    <script src="../_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css?v=a4fa0645" />
+    <script src="../_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="../_static/doctools.js?v=888ff710"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
     <link rel="next" title="Tutorial" href="tutorial.html" />
@@ -33,10 +41,10 @@
           <div class="body" role="main">
             
   <section id="intro">
-<h1>Intro<a class="headerlink" href="#intro" title="Permalink to this heading">¶</a></h1>
+<h1>Intro<a class="headerlink" href="#intro" title="Link to this heading">¶</a></h1>
 </section>
 <section id="autots">
-<h1>AutoTS<a class="headerlink" href="#autots" title="Permalink to this heading">¶</a></h1>
+<h1>AutoTS<a class="headerlink" href="#autots" title="Link to this heading">¶</a></h1>
 <p><span class="raw-html-m2r"><img src="/img/autots_1280.png" width="400" height="184" title="AutoTS Logo"></span></p>
 <p>AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale.</p>
 <p>In 2023, AutoTS has won in the M6 forecasting competition, delivering the highest performance investment decisions across 12 months of stock market forecasting.</p>
@@ -51,7 +59,7 @@ <h1>AutoTS<a class="headerlink" href="#autots" title="Permalink to this heading"
 <p>Horizontal and mosaic style ensembles are the flagship ensembling types, allowing each series to receive the most accurate possible models while still maintaining scalability.</p>
 <p>A combination of metrics and cross-validation options, the ability to apply subsets and weighting, regressor generation tools, simulation forecasting mode, event risk forecasting, live datasets, template import and export, plotting, and a collection of data shaping parameters round out the available feature set.</p>
 <section id="table-of-contents">
-<h2>Table of Contents<a class="headerlink" href="#table-of-contents" title="Permalink to this heading">¶</a></h2>
+<h2>Table of Contents<a class="headerlink" href="#table-of-contents" title="Link to this heading">¶</a></h2>
 <ul class="simple">
 <li><p><a class="reference external" href="https://github.com/winedarksea/AutoTS#installation">Installation</a></p></li>
 <li><p><a class="reference external" href="https://github.com/winedarksea/AutoTS#basic-use">Basic Use</a></p></li>
@@ -61,7 +69,7 @@ <h2>Table of Contents<a class="headerlink" href="#table-of-contents" title="Perm
 </ul>
 </section>
 <section id="id1">
-<h2>Installation<a class="headerlink" href="#id1" title="Permalink to this heading">¶</a></h2>
+<h2>Installation<a class="headerlink" href="#id1" title="Link to this heading">¶</a></h2>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">autots</span>
 </pre></div>
 </div>
@@ -69,7 +77,7 @@ <h2>Installation<a class="headerlink" href="#id1" title="Permalink to this headi
 <p>Be advised there are several other projects that have chosen similar names, so make sure you are on the right AutoTS code, papers, and documentation.</p>
 </section>
 <section id="id2">
-<h2>Basic Use<a class="headerlink" href="#id2" title="Permalink to this heading">¶</a></h2>
+<h2>Basic Use<a class="headerlink" href="#id2" title="Link to this heading">¶</a></h2>
 <p>Input data for AutoTS is expected to come in either a <em>long</em> or a <em>wide</em> format:</p>
 <ul class="simple">
 <li><p>The <em>wide</em> format is a <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> with a <code class="docutils literal notranslate"><span class="pre">pandas.DatetimeIndex</span></code> and each column a distinct series.</p></li>
@@ -133,7 +141,7 @@ <h2>Basic Use<a class="headerlink" href="#id2" title="Permalink to this heading"
 <p>Also take a look at the <a class="reference external" href="https://github.com/winedarksea/AutoTS/blob/master/production_example.py">production_example.py</a></p>
 </section>
 <section id="id3">
-<h2>Tips for Speed and Large Data:<a class="headerlink" href="#id3" title="Permalink to this heading">¶</a></h2>
+<h2>Tips for Speed and Large Data:<a class="headerlink" href="#id3" title="Link to this heading">¶</a></h2>
 <ul class="simple">
 <li><p>Use appropriate model lists, especially the predefined lists:</p>
 <ul>
@@ -172,7 +180,7 @@ <h2>Tips for Speed and Large Data:<a class="headerlink" href="#id3" title="Perma
 </ul>
 </section>
 <section id="how-to-contribute">
-<h2>How to Contribute:<a class="headerlink" href="#how-to-contribute" title="Permalink to this heading">¶</a></h2>
+<h2>How to Contribute:<a class="headerlink" href="#how-to-contribute" title="Link to this heading">¶</a></h2>
 <ul class="simple">
 <li><p>Give feedback on where you find the documentation confusing</p></li>
 <li><p>Use AutoTS and…</p>
@@ -278,21 +286,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/source/modules.html b/docs/build/html/source/modules.html
index bda841f4..02edbd77 100644
--- a/docs/build/html/source/modules.html
+++ b/docs/build/html/source/modules.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="../">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>autots &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
-    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/doctools.js"></script>
-    <script src="../_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css?v=a4fa0645" />
+    <script src="../_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="../_static/doctools.js?v=888ff710"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
     <link rel="next" title="autots package" href="autots.html" />
@@ -33,7 +41,7 @@
           <div class="body" role="main">
             
   <section id="autots">
-<h1>autots<a class="headerlink" href="#autots" title="Permalink to this heading">¶</a></h1>
+<h1>autots<a class="headerlink" href="#autots" title="Link to this heading">¶</a></h1>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="autots.html">autots package</a><ul>
@@ -367,21 +375,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/build/html/source/tutorial.html b/docs/build/html/source/tutorial.html
index 01ca8546..cef15a95 100644
--- a/docs/build/html/source/tutorial.html
+++ b/docs/build/html/source/tutorial.html
@@ -1,17 +1,25 @@
-
 <!DOCTYPE html>
 
-<html lang="en">
+<html lang="en" data-content_root="../">
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
 
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-P2KLF8302E"></script>
+    <script>
+        window.dataLayer = window.dataLayer || [];
+        function gtag(){dataLayer.push(arguments);}
+        gtag('js', new Date());
+        gtag('config', 'G-P2KLF8302E');
+    </script>
+    
     <title>Tutorial &#8212; AutoTS 0.6.10 documentation</title>
-    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
-    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
-    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/doctools.js"></script>
-    <script src="../_static/sphinx_highlight.js"></script>
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=b76e3c8a" />
+    <link rel="stylesheet" type="text/css" href="../_static/alabaster.css?v=a4fa0645" />
+    <script src="../_static/documentation_options.js?v=c6a86a76"></script>
+    <script src="../_static/doctools.js?v=888ff710"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
     <link rel="next" title="autots" href="modules.html" />
@@ -33,12 +41,12 @@
           <div class="body" role="main">
             
   <section id="tutorial">
-<h1>Tutorial<a class="headerlink" href="#tutorial" title="Permalink to this heading">¶</a></h1>
+<h1>Tutorial<a class="headerlink" href="#tutorial" title="Link to this heading">¶</a></h1>
 </section>
 <section id="extended-tutorial">
-<h1>Extended Tutorial<a class="headerlink" href="#extended-tutorial" title="Permalink to this heading">¶</a></h1>
+<h1>Extended Tutorial<a class="headerlink" href="#extended-tutorial" title="Link to this heading">¶</a></h1>
 <section id="table-of-contents">
-<h2>Table of Contents<a class="headerlink" href="#table-of-contents" title="Permalink to this heading">¶</a></h2>
+<h2>Table of Contents<a class="headerlink" href="#table-of-contents" title="Link to this heading">¶</a></h2>
 <ul class="simple">
 <li><p><a class="reference external" href="https://winedarksea.github.io/AutoTS/build/html/source/tutorial.html#id1">A Simple Example</a></p></li>
 <li><p><a class="reference external" href="https://winedarksea.github.io/AutoTS/build/html/source/tutorial.html#id2">Validation and Cross Validation</a></p></li>
@@ -56,7 +64,7 @@ <h2>Table of Contents<a class="headerlink" href="#table-of-contents" title="Perm
 <li><p><a class="reference external" href="https://winedarksea.github.io/AutoTS/build/html/source/tutorial.html#id10">Models</a></p></li>
 </ul>
 <section id="id1">
-<h3>A simple example<a class="headerlink" href="#id1" title="Permalink to this heading">¶</a></h3>
+<h3>A simple example<a class="headerlink" href="#id1" title="Link to this heading">¶</a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># also: _hourly, _daily, _weekly, or _yearly</span>
 <span class="kn">from</span> <span class="nn">autots.datasets</span> <span class="kn">import</span> <span class="n">load_monthly</span>
 
@@ -78,14 +86,14 @@ <h3>A simple example<a class="headerlink" href="#id1" title="Permalink to this h
 </pre></div>
 </div>
 <section id="import-of-data">
-<h4>Import of data<a class="headerlink" href="#import-of-data" title="Permalink to this heading">¶</a></h4>
+<h4>Import of data<a class="headerlink" href="#import-of-data" title="Link to this heading">¶</a></h4>
 <p>There are two shapes/styles of <code class="docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code> which are accepted.
 The first is <em>long</em> data, like that out of an aggregated sales-transaction table containing three columns identified to <code class="docutils literal notranslate"><span class="pre">.fit()</span></code> as <code class="docutils literal notranslate"><span class="pre">date_col</span> <span class="pre">{pd.Datetime},</span> <span class="pre">value_col</span> <span class="pre">{the</span> <span class="pre">numeric</span> <span class="pre">or</span> <span class="pre">categorical</span> <span class="pre">data</span> <span class="pre">of</span> <span class="pre">interest},</span> <span class="pre">and</span> <span class="pre">id_col</span> <span class="pre">{id</span> <span class="pre">string,</span> <span class="pre">if</span> <span class="pre">multiple</span> <span class="pre">series</span> <span class="pre">are</span> <span class="pre">provided}</span></code>.
 Alternatively, the data may be in a <em>wide</em> format where the index is a <code class="docutils literal notranslate"><span class="pre">pandas.DatetimeIndex</span></code>, and each column is a distinct data series.</p>
 <p>If horizontal style ensembles are used, series_ids/column names will be coerced to strings.</p>
 </section>
 <section id="you-can-tailor-the-process-in-a-few-ways">
-<h4>You can tailor the process in a few ways…<a class="headerlink" href="#you-can-tailor-the-process-in-a-few-ways" title="Permalink to this heading">¶</a></h4>
+<h4>You can tailor the process in a few ways…<a class="headerlink" href="#you-can-tailor-the-process-in-a-few-ways" title="Link to this heading">¶</a></h4>
 <p>The simplest way to improve accuracy is to increase the number of generations <code class="docutils literal notranslate"><span class="pre">max_generations=15</span></code>. Each generation tries new models, taking additional time but improving the accuracy. The nature of genetic algorithms, however, means there is no consistent improvement for each generation, and large number of generations will often only result in minimal performance gains.</p>
 <p>Another approach that may improve accuracy is to set <code class="docutils literal notranslate"><span class="pre">ensemble='all'</span></code>. Ensemble parameter expects a single string, and can for example be <code class="docutils literal notranslate"><span class="pre">'simple,dist'</span></code>, or <code class="docutils literal notranslate"><span class="pre">'horizontal'</span></code>. As this means storing more details of every model, this takes more time and memory.</p>
 <p>A handy parameter for when your data is expected to always be 0 or greater (such as unit sales) is to set <code class="docutils literal notranslate"><span class="pre">no_negatives=True</span></code>. This forces forecasts to be greater than or equal to 0.
@@ -102,7 +110,7 @@ <h4>You can tailor the process in a few ways…<a class="headerlink" href="#you-
 </section>
 </section>
 <section id="what-to-worry-about">
-<h3>What to Worry About<a class="headerlink" href="#what-to-worry-about" title="Permalink to this heading">¶</a></h3>
+<h3>What to Worry About<a class="headerlink" href="#what-to-worry-about" title="Link to this heading">¶</a></h3>
 <p>There are some basic things to beware of that can commonly lead to poor results:</p>
 <ol class="arabic simple">
 <li><p>Bad data (sudden drops or missing values) in the <em>most recent</em> data is the single most common cause of bad forecasts here. As many models use the most recent data as a jumping off point, error in the most recent data points can have an oversized effect on forecasts.</p></li>
@@ -113,7 +121,7 @@ <h3>What to Worry About<a class="headerlink" href="#what-to-worry-about" title="
 <p>What you don’t need to do before the automated forecasting is any typical preprocessing. It is best to leave it up to the model selection process to choose, as different models do better with different types of preprocessing.</p>
 </section>
 <section id="id2">
-<h3>Validation and Cross Validation<a class="headerlink" href="#id2" title="Permalink to this heading">¶</a></h3>
+<h3>Validation and Cross Validation<a class="headerlink" href="#id2" title="Link to this heading">¶</a></h3>
 <p>Cross validation helps assure that the optimal model is stable over the dynamics of a time series.
 Cross validation can be tricky in time series data due to the necessity of preventing data leakage from future data points.</p>
 <p>Firstly, all models are initially validated on the most recent piece of data. This is done because the most recent data will generally most closely resemble the forecast future.
@@ -138,7 +146,7 @@ <h3>Validation and Cross Validation<a class="headerlink" href="#id2" title="Perm
 In these cases, avoid the <code class="docutils literal notranslate"><span class="pre">even</span></code> cross validation and use one of the other validation methods.</p>
 </section>
 <section id="id3">
-<h3>Another Example:<a class="headerlink" href="#id3" title="Permalink to this heading">¶</a></h3>
+<h3>Another Example:<a class="headerlink" href="#id3" title="Link to this heading">¶</a></h3>
 <p>Here, we are forecasting the traffice along Interstate 94 between Minneapolis and St Paul in Minnesota. This is a great dataset to demonstrate a recommended way of including external variables - by including them as time series with a lower weighting.
 Here weather data is included - winter and road construction being the major influencers for traffic and will be forecast alongside the traffic volume. These additional series carry information to models such as <code class="docutils literal notranslate"><span class="pre">RollingRegression</span></code>, <code class="docutils literal notranslate"><span class="pre">VARMAX</span></code>, and <code class="docutils literal notranslate"><span class="pre">VECM</span></code>.</p>
 <p>Also seen in use here is the <code class="docutils literal notranslate"><span class="pre">model_list</span></code>.</p>
@@ -189,14 +197,14 @@ <h3>Another Example:<a class="headerlink" href="#id3" title="Permalink to this h
 </div>
 </section>
 <section id="id4">
-<h3>Model Lists<a class="headerlink" href="#id4" title="Permalink to this heading">¶</a></h3>
+<h3>Model Lists<a class="headerlink" href="#id4" title="Link to this heading">¶</a></h3>
 <p>By default, most available models are tried. For a more limited subset of models, a custom list can be passed in, or more simply, a string, one of <code class="docutils literal notranslate"><span class="pre">'probabilistic',</span> <span class="pre">'multivariate',</span> <span class="pre">'fast',</span> <span class="pre">'superfast',</span> <span class="pre">or</span> <span class="pre">'all'</span></code>.</p>
 <p>A table of all available models is below.</p>
 <p>On large multivariate series, <code class="docutils literal notranslate"><span class="pre">DynamicFactor</span></code> and <code class="docutils literal notranslate"><span class="pre">VARMAX</span></code> can be impractically slow.</p>
 </section>
 </section>
 <section id="deployment-and-template-import-export">
-<h2>Deployment and Template Import/Export<a class="headerlink" href="#deployment-and-template-import-export" title="Permalink to this heading">¶</a></h2>
+<h2>Deployment and Template Import/Export<a class="headerlink" href="#deployment-and-template-import-export" title="Link to this heading">¶</a></h2>
 <p>Take a look at the <a class="reference external" href="https://github.com/winedarksea/AutoTS/blob/master/production_example.py">production_example.py</a></p>
 <p>Many models can be reverse engineered with (relative) simplicity outside of AutoTS by placing the choosen parameters into Statsmodels or other underlying package.
 Following the model training, the top models can be exported to a <code class="docutils literal notranslate"><span class="pre">.csv</span></code> or <code class="docutils literal notranslate"><span class="pre">.json</span></code> file, then on next run only those models will be tried.
@@ -216,7 +224,7 @@ <h2>Deployment and Template Import/Export<a class="headerlink" href="#deployment
 </pre></div>
 </div>
 <section id="id5">
-<h3>Running Just One Model<a class="headerlink" href="#id5" title="Permalink to this heading">¶</a></h3>
+<h3>Running Just One Model<a class="headerlink" href="#id5" title="Link to this heading">¶</a></h3>
 <p>While the above version of deployment, with  evolving templates and cross_validation on every run, is the recommended deployment, it is also possible to run a single fixed model.</p>
 <p>Coming from the deeper internals of AutoTS, this function can only take the <code class="docutils literal notranslate"><span class="pre">wide</span></code> style data (there is a long_to_wide function available).
 Data must already be fairly clean - all numerics (or np.nan).
@@ -256,7 +264,7 @@ <h3>Running Just One Model<a class="headerlink" href="#id5" title="Permalink to
 <p>If you overwrite these, it will accordingly change the forecast output.</p>
 </section>
 <section id="id6">
-<h3>Metrics<a class="headerlink" href="#id6" title="Permalink to this heading">¶</a></h3>
+<h3>Metrics<a class="headerlink" href="#id6" title="Link to this heading">¶</a></h3>
 <p>There are a number of available metrics, all combined together into a ‘Score’ which evaluates the best model. The ‘Score’ that compares models can easily be adjusted by passing through custom metric weights dictionary.
 Higher weighting increases the importance of that metric, while 0 removes that metric from consideration. Weights must be numbers greater than or equal to 0.
 This weighting is not to be confused with series weighting, which effects how equally any one metric is applied to all the series.</p>
@@ -340,7 +348,7 @@ <h3>Metrics<a class="headerlink" href="#id6" title="Permalink to this heading">
 </div>
 </section>
 <section id="hierarchial-and-grouped-forecasts">
-<h3>Hierarchial and Grouped Forecasts<a class="headerlink" href="#hierarchial-and-grouped-forecasts" title="Permalink to this heading">¶</a></h3>
+<h3>Hierarchial and Grouped Forecasts<a class="headerlink" href="#hierarchial-and-grouped-forecasts" title="Link to this heading">¶</a></h3>
 <p>Hiearchial and grouping refer to multivariate forecast situations where the individual series are aggregated.
 A common example of this is product sales forecasting, where individual products are forecast and then also aggregated for a view on demand across all products.
 Aggregation combines the errors of individual series, however, potentially resulting in major over- or -under estimation of the overall demand.
@@ -354,7 +362,7 @@ <h3>Hierarchial and Grouped Forecasts<a class="headerlink" href="#hierarchial-an
 Additionally, <code class="docutils literal notranslate"><span class="pre">MLE</span></code> or <code class="docutils literal notranslate"><span class="pre">iMLE</span></code> can be used if either underestimation or overestimation respectively has been identified as a problem.</p>
 </section>
 <section id="id7">
-<h3>Ensembles<a class="headerlink" href="#id7" title="Permalink to this heading">¶</a></h3>
+<h3>Ensembles<a class="headerlink" href="#id7" title="Link to this heading">¶</a></h3>
 <p>Ensemble methods are specified by the <code class="docutils literal notranslate"><span class="pre">ensemble=</span></code> parameter. It can be either a list or a comma-separated string.</p>
 <p><code class="docutils literal notranslate"><span class="pre">simple</span></code> style ensembles (labeled ‘BestN’ in templates) are the most recognizable form of ensemble and are the simple average of the specified models, here usally 3 or 5 models.
 <code class="docutils literal notranslate"><span class="pre">distance</span></code> style ensembles are two models spliced together. The first model forecasts the first fraction of forecast period, the second model the latter half. There is no overlap of the models.
@@ -393,14 +401,14 @@ <h3>Ensembles<a class="headerlink" href="#id7" title="Permalink to this heading"
 </section>
 </section>
 <section id="installation-and-dependency-versioning">
-<h2>Installation and Dependency Versioning<a class="headerlink" href="#installation-and-dependency-versioning" title="Permalink to this heading">¶</a></h2>
+<h2>Installation and Dependency Versioning<a class="headerlink" href="#installation-and-dependency-versioning" title="Link to this heading">¶</a></h2>
 <p><code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">autots</span></code></p>
 <p>Some optional packages require installing <a class="reference external" href="https://visualstudio.microsoft.com/visual-cpp-build-tools/">Visual Studio C compilers</a> if on Windows.</p>
 <p>On Linux systems, apt-get/yum (rather than pip) installs of numpy/pandas may install faster/more stable compilations.
 Linux may also require <code class="docutils literal notranslate"><span class="pre">sudo</span> <span class="pre">apt</span> <span class="pre">install</span> <span class="pre">build-essential</span></code> for some packages.</p>
 <p>You can check if your system is using mkl, OpenBLAS, or none with <code class="docutils literal notranslate"><span class="pre">numpy.show_config()</span></code>. Generally recommended that you double-check this after installing new packages to make sure you haven’t broken the LINPACK connection.</p>
 <section id="requirements">
-<h3>Requirements:<a class="headerlink" href="#requirements" title="Permalink to this heading">¶</a></h3>
+<h3>Requirements:<a class="headerlink" href="#requirements" title="Link to this heading">¶</a></h3>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span>Python &gt;= 3.6
 numpy
     &gt;= 1.20 (Sliding Window in Motif and WindowRegression)
@@ -430,7 +438,7 @@ <h3>Requirements:<a class="headerlink" href="#requirements" title="Permalink to
 <p><code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">autots['additional']</span></code></p>
 </section>
 <section id="optional-packages">
-<h3>Optional Packages<a class="headerlink" href="#optional-packages" title="Permalink to this heading">¶</a></h3>
+<h3>Optional Packages<a class="headerlink" href="#optional-packages" title="Link to this heading">¶</a></h3>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">requests</span>
 <span class="n">psutil</span>
 <span class="n">holidays</span>
@@ -452,7 +460,7 @@ <h3>Optional Packages<a class="headerlink" href="#optional-packages" title="Perm
 </div>
 <p>Tensorflow, LightGBM, and XGBoost bring powerful models, but are also among the slowest. If speed is a concern, not installing them will speed up ~Regression style model runs.</p>
 <section id="safest-bet-for-installation">
-<h4>Safest bet for installation:<a class="headerlink" href="#safest-bet-for-installation" title="Permalink to this heading">¶</a></h4>
+<h4>Safest bet for installation:<a class="headerlink" href="#safest-bet-for-installation" title="Link to this heading">¶</a></h4>
 <p>venv, Anaconda, or <a class="reference external" href="https://github.com/conda-forge/miniforge/">Miniforge</a> with some more tips <a class="reference external" href="https://syllepsis.live/2022/01/17/setting-up-and-optimizing-python-for-data-science-on-intel-amd-and-arm-including-apple-computers/">here</a>.</p>
 <div class="highlight-shell notranslate"><div class="highlight"><pre><span></span><span class="c1"># create a conda or venv environment</span>
 conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>timeseries<span class="w"> </span><span class="nv">python</span><span class="o">=</span><span class="m">3</span>.9
@@ -500,7 +508,7 @@ <h4>Safest bet for installation:<a class="headerlink" href="#safest-bet-for-inst
 <p><code class="docutils literal notranslate"><span class="pre">mamba</span></code> and <code class="docutils literal notranslate"><span class="pre">conda</span></code> commands are generally interchangeable. <code class="docutils literal notranslate"><span class="pre">conda</span> <span class="pre">env</span> <span class="pre">remove</span> <span class="pre">-n</span> <span class="pre">env_name</span></code></p>
 </section>
 <section id="intel-conda-channel-installation-sometime-faster-also-more-prone-to-bugs">
-<h4>Intel conda channel installation (sometime faster, also, more prone to bugs)<a class="headerlink" href="#intel-conda-channel-installation-sometime-faster-also-more-prone-to-bugs" title="Permalink to this heading">¶</a></h4>
+<h4>Intel conda channel installation (sometime faster, also, more prone to bugs)<a class="headerlink" href="#intel-conda-channel-installation-sometime-faster-also-more-prone-to-bugs" title="Link to this heading">¶</a></h4>
 <p><a class="reference external" href="https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html">https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html</a></p>
 <div class="highlight-shell notranslate"><div class="highlight"><pre><span></span><span class="c1"># create the environment</span>
 mamba<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>aikit37<span class="w"> </span><span class="nv">python</span><span class="o">=</span><span class="m">3</span>.7<span class="w"> </span>intel-aikit-modin<span class="w"> </span>pandas<span class="w"> </span>statsmodels<span class="w"> </span>prophet<span class="w"> </span>numexpr<span class="w"> </span>bottleneck<span class="w"> </span>tqdm<span class="w"> </span>holidays<span class="w"> </span>lightgbm<span class="w"> </span>matplotlib<span class="w"> </span>requests<span class="w"> </span>tensorflow<span class="w"> </span>dpctl<span class="w"> </span>-c<span class="w"> </span>intel
@@ -521,7 +529,7 @@ <h4>Intel conda channel installation (sometime faster, also, more prone to bugs)
 </section>
 </section>
 <section id="speed-benchmark">
-<h3>Speed Benchmark<a class="headerlink" href="#speed-benchmark" title="Permalink to this heading">¶</a></h3>
+<h3>Speed Benchmark<a class="headerlink" href="#speed-benchmark" title="Link to this heading">¶</a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">autots.evaluator.benchmark</span> <span class="kn">import</span> <span class="n">Benchmark</span>
 <span class="n">bench</span> <span class="o">=</span> <span class="n">Benchmark</span><span class="p">()</span>
 <span class="n">bench</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span> <span class="n">times</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
@@ -531,9 +539,9 @@ <h3>Speed Benchmark<a class="headerlink" href="#speed-benchmark" title="Permalin
 </section>
 </section>
 <section id="caveats-and-advice">
-<h2>Caveats and Advice<a class="headerlink" href="#caveats-and-advice" title="Permalink to this heading">¶</a></h2>
+<h2>Caveats and Advice<a class="headerlink" href="#caveats-and-advice" title="Link to this heading">¶</a></h2>
 <section id="mysterious-crashes">
-<h3>Mysterious crashes<a class="headerlink" href="#mysterious-crashes" title="Permalink to this heading">¶</a></h3>
+<h3>Mysterious crashes<a class="headerlink" href="#mysterious-crashes" title="Link to this heading">¶</a></h3>
 <p>Usually mysterious crashes or hangs (those without clear error messages) occur when the CPU or Memory is overloaded.
 <code class="docutils literal notranslate"><span class="pre">UnivariateRegression</span></code> is usually the most prone to these issues, removing it from the model_list may help (by default it is not included in most lists for this reason).</p>
 <p>Try setting <code class="docutils literal notranslate"><span class="pre">n_jobs=1</span></code> or an otherwise low number, which should reduce the load. Also test the ‘superfast’ naive models, which are generally low resource consumption.
@@ -542,18 +550,18 @@ <h3>Mysterious crashes<a class="headerlink" href="#mysterious-crashes" title="Pe
 <p>Rebooting between heavy uses of multiprocessing can also help reduce the risk of crashing in future model runs.</p>
 </section>
 <section id="series-ids-really-need-to-be-unique-or-column-names-need-to-be-all-unique-in-wide-data">
-<h3>Series IDs really need to be unique (or column names need to be all unique in wide data)<a class="headerlink" href="#series-ids-really-need-to-be-unique-or-column-names-need-to-be-all-unique-in-wide-data" title="Permalink to this heading">¶</a></h3>
+<h3>Series IDs really need to be unique (or column names need to be all unique in wide data)<a class="headerlink" href="#series-ids-really-need-to-be-unique-or-column-names-need-to-be-all-unique-in-wide-data" title="Link to this heading">¶</a></h3>
 <p>Pretty much as it says, if this isn’t true, some odd things may happen that shouldn’t.</p>
 <p>Also if using the Prophet model, you can’t have any series named ‘ds’</p>
 </section>
 <section id="short-training-history">
-<h3>Short Training History<a class="headerlink" href="#short-training-history" title="Permalink to this heading">¶</a></h3>
+<h3>Short Training History<a class="headerlink" href="#short-training-history" title="Link to this heading">¶</a></h3>
 <p>How much data is ‘too little’ depends on the seasonality and volatility of the data.
 Minimal training data most greatly impacts the ability to do proper cross validation. Set <code class="docutils literal notranslate"><span class="pre">num_validations=0</span></code> in such cases.
 Since ensembles are based on the test dataset, it would also be wise to set <code class="docutils literal notranslate"><span class="pre">ensemble=None</span></code> if <code class="docutils literal notranslate"><span class="pre">num_validations=0</span></code>.</p>
 </section>
 <section id="adding-regressors-and-other-information">
-<h3>Adding regressors and other information<a class="headerlink" href="#adding-regressors-and-other-information" title="Permalink to this heading">¶</a></h3>
+<h3>Adding regressors and other information<a class="headerlink" href="#adding-regressors-and-other-information" title="Link to this heading">¶</a></h3>
 <p><code class="docutils literal notranslate"><span class="pre">future_</span></code> regressor, to make it clear this is data that will be know with high certainy about the future.
 Such data about the future is rare, one example might be number of stores that will be (planned to be) open each given day in the future when forecast sales.
 Generally using regressors is very helpful for separating ‘organic’ and ‘inorganic’ patterns.
@@ -611,7 +619,7 @@ <h3>Adding regressors and other information<a class="headerlink" href="#adding-r
 </section>
 </section>
 <section id="id8">
-<h2>Simulation Forecasting<a class="headerlink" href="#id8" title="Permalink to this heading">¶</a></h2>
+<h2>Simulation Forecasting<a class="headerlink" href="#id8" title="Link to this heading">¶</a></h2>
 <p>Simulation forecasting allows for experimenting with different potential future scenarios to examine the potential effects on the forecast.
 This is done here by passing known values of a <code class="docutils literal notranslate"><span class="pre">future_regressor</span></code> to model <code class="docutils literal notranslate"><span class="pre">.fit</span></code> and then running <code class="docutils literal notranslate"><span class="pre">.predict</span></code> with multiple variations on the <code class="docutils literal notranslate"><span class="pre">future_regressor</span></code> future values.
 By default in AutoTS, when a <code class="docutils literal notranslate"><span class="pre">future_regressor</span></code> is supplied, models that can utilize it are tried both with and without the regressor.
@@ -661,7 +669,7 @@ <h2>Simulation Forecasting<a class="headerlink" href="#id8" title="Permalink to
 or to try with a subset of the regressor model list like <code class="docutils literal notranslate"><span class="pre">['FBProphet',</span> <span class="pre">'GLM',</span> <span class="pre">'ARDL',</span> <span class="pre">'DatepartRegression']</span></code>.</p>
 </section>
 <section id="event-risk-forecasting-and-anomaly-detection">
-<h2>Event Risk Forecasting and Anomaly Detection<a class="headerlink" href="#event-risk-forecasting-and-anomaly-detection" title="Permalink to this heading">¶</a></h2>
+<h2>Event Risk Forecasting and Anomaly Detection<a class="headerlink" href="#event-risk-forecasting-and-anomaly-detection" title="Link to this heading">¶</a></h2>
 <p>Anomaly (or Outlier) Detection is historic and Event Risk Forecasting is forward looking.</p>
 <p>Event Risk Forecasting
 Generate a risk score (0 to 1, but usually close to 0) for a future event exceeding user specified upper or lower bounds.</p>
@@ -773,7 +781,7 @@ <h2>Event Risk Forecasting and Anomaly Detection<a class="headerlink" href="#eve
 </pre></div>
 </div>
 <section id="a-hack-for-passing-in-parameters-that-aren-t-otherwise-available">
-<h3>A Hack for Passing in Parameters (that aren’t otherwise available)<a class="headerlink" href="#a-hack-for-passing-in-parameters-that-aren-t-otherwise-available" title="Permalink to this heading">¶</a></h3>
+<h3>A Hack for Passing in Parameters (that aren’t otherwise available)<a class="headerlink" href="#a-hack-for-passing-in-parameters-that-aren-t-otherwise-available" title="Link to this heading">¶</a></h3>
 <p>There are a lot of parameters available here, but not always all of the options available for a particular parameter are actually used in generated templates.
 Usually, very slow options are left out. If you are familiar with a model, you can try manualy adding those parameter values in for a run in this way…
 To clarify, you can’t usually add in entirely new parameters in this way, but you can often pass in new choices for existing parameter values.</p>
@@ -785,19 +793,19 @@ <h3>A Hack for Passing in Parameters (that aren’t otherwise available)<a class
 </ol>
 </section>
 <section id="categorical-data">
-<h3>Categorical Data<a class="headerlink" href="#categorical-data" title="Permalink to this heading">¶</a></h3>
+<h3>Categorical Data<a class="headerlink" href="#categorical-data" title="Link to this heading">¶</a></h3>
 <p>Categorical data is handled, but it is handled crudely. For example, optimization metrics do not currently include any categorical accuracy metrics.
 For categorical data that has a meaningful order (ie ‘low’, ‘medium’, ‘high’) it is best for the user to encode that data before passing it in,
 thus properly capturing the relative sequence (ie ‘low’=1, ‘medium’=2, ‘high’=3).</p>
 </section>
 <section id="custom-and-unusual-frequencies">
-<h3>Custom and Unusual Frequencies<a class="headerlink" href="#custom-and-unusual-frequencies" title="Permalink to this heading">¶</a></h3>
+<h3>Custom and Unusual Frequencies<a class="headerlink" href="#custom-and-unusual-frequencies" title="Link to this heading">¶</a></h3>
 <p>Data must be coercible to a regular frequency. It is recommended the frequency be specified as a datetime offset as per pandas documentation: <a class="reference external" href="https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#dateoffset-objects">https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#dateoffset-objects</a>
 Some models will support a more limited range of frequencies.</p>
 </section>
 </section>
 <section id="using-the-transformers-independently">
-<h2>Using the Transformers independently<a class="headerlink" href="#using-the-transformers-independently" title="Permalink to this heading">¶</a></h2>
+<h2>Using the Transformers independently<a class="headerlink" href="#using-the-transformers-independently" title="Link to this heading">¶</a></h2>
 <p>The transformers expect data only in the <code class="docutils literal notranslate"><span class="pre">wide</span></code> shape with ascending date.
 The simplest way to access them is through the <a class="reference external" href="https://winedarksea.github.io/AutoTS/build/html/source/autots.tools.html#autots.tools.transform.GeneralTransformer">GeneralTransformer</a>.
 This takes dictionaries containing strings of the desired transformers and parameters.</p>
@@ -824,7 +832,7 @@ <h2>Using the Transformers independently<a class="headerlink" href="#using-the-t
 </pre></div>
 </div>
 <section id="note-on-regression-models">
-<h3>Note on ~Regression Models<a class="headerlink" href="#note-on-regression-models" title="Permalink to this heading">¶</a></h3>
+<h3>Note on ~Regression Models<a class="headerlink" href="#note-on-regression-models" title="Link to this heading">¶</a></h3>
 <p>The Regression models are WindowRegression, RollingRegression, UnivariateRegression, MultivariateRegression, and DatepartRegression.
 They are all different ways of reshaping the time series into X and Y for traditional ML and Deep Learning approaches.
 All draw from the same potential pool of models, mostly sklearn and tensorflow models.</p>
@@ -839,7 +847,7 @@ <h3>Note on ~Regression Models<a class="headerlink" href="#note-on-regression-mo
 </section>
 </section>
 <section id="id9">
-<h2>Models<a class="headerlink" href="#id9" title="Permalink to this heading">¶</a></h2>
+<h2>Models<a class="headerlink" href="#id9" title="Link to this heading">¶</a></h2>
 <table class="docutils align-default">
 <thead>
 <tr class="row-odd"><th class="head"><p>Model</p></th>
@@ -1399,21 +1407,5 @@ <h3 id="searchlabel">Quick search</h3>
     
 
     
-    <script type="text/javascript">
-
-      var _gaq = _gaq || [];
-      _gaq.push(['_setAccount', 'G-P2KLF8302E']);
-      _gaq.push(['_setDomainName', 'none']);
-      _gaq.push(['_setAllowLinker', true]);
-      _gaq.push(['_trackPageview']);
-
-      (function() {
-        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-      })();
-
-    </script>
-    
   </body>
 </html>
\ No newline at end of file
diff --git a/docs/conf.py b/docs/conf.py
index 479d235a..c02c7f4c 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -34,7 +34,7 @@
 # ones.
 # Add napoleon to the extensions list
 # 'recommonmark',
-extensions = ['sphinx.ext.napoleon', 'sphinx.ext.autodoc', 'm2r2', 'sphinx.ext.githubpages',]
+extensions = ['sphinx.ext.napoleon', 'sphinx.ext.autodoc', 'm2r2', 'sphinx.ext.githubpages', "sphinxcontrib.googleanalytics"]
 
 source_suffix = ['.rst', '.md']
 
@@ -64,7 +64,6 @@
 
 html_theme_options = {
     "show_powered_by": False,
-	'analytics_id': 'G-P2KLF8302E',
 	'logo': 'autots_logo.png',
 	'description': 'Automated Forecasting',
     "github_user": "winedarksea",
@@ -73,5 +72,13 @@
     "show_related": False,
     "note_bg": "#FFF59C",
 }
+
+# pip install sphinxcontrib-googleanalytics
+googleanalytics_id = "G-P2KLF8302E"
+# this will give a warning but works at least with pydata theme
+html_theme_options["analytics"] = {
+    "google_analytics_id": googleanalytics_id,
+}
+
 # Output file base name for HTML help builder.
 htmlhelp_basename = "autotsdoc"
\ No newline at end of file