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). 'vtreat::prepare' should be used as you would use 'model.matrix'.

Maintainer: John Mount <jmount at win-vector.com>

Author(s): John Mount, Nina Zumel

Install package and any missing dependencies by running this line in your R console:

install.packages("vtreat")

Depends
Imports
Suggests testthat, knitr, parallel, rmarkdown, dplyr, ggplot2, RSQLite
Enhances
Linking to
Reverse
depends
Reverse
imports
Reverse
suggests
Reverse
enhances
Reverse
linking to

Package vtreat
Materials
URL https://github.com/WinVector/vtreat
Task Views
Version 0.5.30
Published 2017-01-21
License GPL-3
BugReports https://github.com/WinVector/vtreat/issues
SystemRequirements
NeedsCompilation no
Citation
CRAN checks vtreat check results
Package source vtreat_0.5.30.tar.gz