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>.
| Version: | 1.6.0 |
| Depends: | R (≥ 3.4.0), wrapr (≥ 1.9.6) |
| Imports: | stats, digest |
| Suggests: | rquery (≥ 1.4.4), rqdatatable (≥ 1.2.7), data.table (≥ 1.12.2), isotone, lme4, knitr, rmarkdown, parallel, DBI, RSQLite, datasets, R.rsp, RUnit |
| Published: | 2020-03-11 |
| Author: | John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph] |
| Maintainer: | John Mount <jmount at win-vector.com> |
| BugReports: | https://github.com/WinVector/vtreat/issues |
| License: | GPL-2 | GPL-3 |
| URL: | https://github.com/WinVector/vtreat/, https://winvector.github.io/vtreat/ |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | vtreat results |
| Reference manual: | vtreat.pdf |
| Vignettes: |
Multi Class vtreat Saving Treatment Plans vtreat Variable Importance vtreat package vtreat cross frames vtreat grouping example vtreat overfit vtreat Rare Levels vtreat scale mode vtreat significance vtreat data splitting Variable Types vtreat Formal Article |
| Package source: | vtreat_1.6.0.tar.gz |
| Windows binaries: | r-devel: vtreat_1.6.0.zip, r-release: vtreat_1.6.0.zip, r-oldrel: vtreat_1.6.0.zip |
| macOS binaries: | r-release: vtreat_1.6.0.tgz, r-oldrel: vtreat_1.6.0.tgz |
| Old sources: | vtreat archive |
| Reverse imports: | crispRdesignR |
Please use the canonical form https://CRAN.R-project.org/package=vtreat to link to this page.