DESCRIPTION

Package: vtreat
Type: Package
Title: A Statistically Sound 'data.frame' Processor/Conditioner
Version: 1.6.5
Date: 2024-06-12
Authors@R: c(
    person("John", "Mount", email = "jmount@win-vector.com", role = c("aut", "cre")),
    person("Nina", "Zumel", email = "nzumel@win-vector.com", role = c("aut")),
    person(family = "Win-Vector LLC", role = c("cph"))
    )
URL: https://github.com/WinVector/vtreat/, https://winvector.github.io/vtreat/
BugReports: https://github.com/WinVector/vtreat/issues
Maintainer: John Mount <jmount@win-vector.com>
Description: A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner.
    'vtreat' prepares variables so that data has fewer exceptional cases, making
    it easier to safely use models in production. Common problems 'vtreat' defends
    against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new
    categorical levels (levels seen during application, but not during training). Reference: 
    "'vtreat': a data.frame Processor for Predictive Modeling", Zumel, Mount, 2016, <DOI:10.5281/zenodo.1173313>.
License: GPL-2 | GPL-3
Depends: 
  R (>= 3.4.0),
  wrapr (>= 2.1.0)
Imports: 
    stats,
    digest
Suggests: 
    rquery (>= 1.4.99),
    rqdatatable (>= 1.3.3),
    data.table (>= 1.12.2),
    knitr,
    rmarkdown,
    parallel,
    DBI,
    RSQLite,
    datasets,
    R.rsp,
    tinytest
VignetteBuilder: knitr, R.rsp
RoxygenNote: 7.3.1
ByteCompile: true