vtreat: A Statistically Sound 'data.frame' Processor/Conditioner

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.1173314.

Version: 1.2.3
Depends: R (≥ 3.2.1)
Imports: stats, wrapr (≥ 1.5.0)
Suggests: rquery (≥ 0.5.0), rqdatatable, testthat, knitr, parallel, rmarkdown, data.table, ggplot2, DBI, RSQLite, datasets
Published: 2018-07-11
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount at win-vector.com>
BugReports: https://github.com/WinVector/vtreat/issues
License: GPL-3
URL: https://github.com/WinVector/vtreat/, https://winvector.github.io/vtreat/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: vtreat results


Reference manual: vtreat.pdf
Vignettes: Saving Treatment Plans
vtreat package
vtreat cross frames
vtreat grouping example
vtreat overfit
vtreat Rare Levels
vtreat scale mode
vtreat significance
vtreat data splitting
Variable Types
Package source: vtreat_1.2.3.tar.gz
Windows binaries: r-devel: vtreat_1.2.3.zip, r-release: vtreat_1.2.3.zip, r-oldrel: vtreat_1.2.3.zip
OS X binaries: r-release: vtreat_1.2.3.tgz, r-oldrel: vtreat_1.2.3.tgz
Old sources: vtreat archive


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