WinVector/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>.
Getting started
Browse package contents
Package details |
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| Maintainer | John Mount <jmount@win-vector.com> |
| License | GPL-2 | GPL-3 |
| Version | 1.6.4 |
| URL | https://github.com/WinVector/vtreat/ https://winvector.github.io/vtreat/ |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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