WinVector/vtreat: A Statistically Sound 'data.frame' Processor/Conditioner
Version 1.3.1

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.

Getting started

Package details

MaintainerJohn Mount <[email protected]>
LicenseGPL-3
Version1.3.1
URL https://github.com/WinVector/vtreat/ https://winvector.github.io/vtreat/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("WinVector/vtreat")
WinVector/vtreat documentation built on Aug. 9, 2018, 4:23 a.m.