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Merge pull request #122 from tidymodels/rc-0.0.4
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Rc 0.0.4
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DavisVaughan authored Sep 3, 2019
2 parents 880b61b + 2c4247c commit 5c5d2de
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2 changes: 2 additions & 0 deletions CRAN-RELEASE
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This package was submitted to CRAN on 2019-08-26.
Once it is accepted, delete this file and tag the release (commit 5bb75fc46d).
2 changes: 1 addition & 1 deletion DESCRIPTION
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@@ -1,7 +1,7 @@
Package: yardstick
Type: Package
Title: Tidy Characterizations of Model Performance
Version: 0.0.3.9000
Version: 0.0.4
Authors@R: c(
person("Max", "Kuhn", , "max@rstudio.com", c("aut")),
person("Davis", "Vaughan", , "davis@rstudio.com", c("aut", "cre")),
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2 changes: 1 addition & 1 deletion NEWS.md
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# yardstick (development version)
# yardstick 0.0.4

## New metrics and functionality

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2 changes: 2 additions & 0 deletions R/metrics.R
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Expand Up @@ -348,6 +348,7 @@ make_prob_class_metric_function <- function(fns) {

class(metric_function) <- c(
"class_prob_metric_set",
"metric_set",
class(metric_function)
)

Expand Down Expand Up @@ -387,6 +388,7 @@ make_numeric_metric_function <- function(fns) {

class(metric_function) <- c(
"numeric_metric_set",
"metric_set",
class(metric_function)
)

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9 changes: 2 additions & 7 deletions cran-comments.md
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## Comments

This is a small release mainly to resolve failing tests on CRAN. In particular, we have fixed:
- "unable to re-encode" warnings
- Failing tests due to R 3.6 `sample()` changes
- An issue with an old release of R and dplyr 0.8.0.1 causing factors to be coerced to integers

It also introduces a few new metrics, and squashes a few non-CRAN related bugs.
This is a small release with a few new metrics, and a few squashed bugs.

## Test environments
* local OS X install, R 3.5.2
* local OS X install, R 3.6.0
* ubuntu 14.04 (on travis-ci) (devel and release)
* win-builder (devel and release)

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8 changes: 8 additions & 0 deletions tests/testthat/test_metrics.R
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Expand Up @@ -135,6 +135,14 @@ test_that('metric set functions are classed', {
metric_set(mae),
"numeric_metric_set"
)
expect_is(
metric_set(accuracy, roc_auc),
"metric_set"
)
expect_is(
metric_set(mae),
"metric_set"
)
})

test_that('metric set functions retain class/prob metric functions', {
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