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.1173313>.

Package details

AuthorJohn Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
MaintainerJohn Mount <jmount@win-vector.com>
LicenseGPL-2 | GPL-3
Version1.6.3
URL https://github.com/WinVector/vtreat/ https://winvector.github.io/vtreat/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("vtreat")

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vtreat documentation built on June 11, 2021, 5:13 p.m.