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. 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, new categorical levels (levels seen during application, but not during training). 'vtreat::prepare' should be used as you would use 'model.matrix'.

Version: 0.5.28
Suggests: testthat, knitr, parallel, rmarkdown, dplyr, ggplot2
Published: 2016-10-25
Author: John Mount, Nina Zumel
Maintainer: John Mount <jmount at win-vector.com>
BugReports: https://github.com/WinVector/vtreat/issues
License: GPL-3
URL: https://github.com/WinVector/vtreat
NeedsCompilation: no
Materials: README
CRAN checks: vtreat results


Reference manual: vtreat.pdf
Vignettes: 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_0.5.28.tar.gz
Windows binaries: r-devel: vtreat_0.5.28.zip, r-release: vtreat_0.5.28.zip, r-oldrel: vtreat_0.5.28.zip
OS X Mavericks binaries: r-release: vtreat_0.5.28.tgz, r-oldrel: vtreat_0.5.28.tgz
Old sources: vtreat archive


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