A Statistically Sound 'data.frame' Processor/Conditioner R package vtreat version 1.6.5 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>. Software Depends: R (>= 3.4.0), wrapr (>= 2.1.0) Imports: stats, digest Suggests: rquery (>= 1.4.99), rqdatatable (>= 1.3.3), data.table (>= 1.12.2), knitr, rmarkdown, parallel, DBI, RSQLite, datasets, R.rsp, tinytest John Mount <jmount@win-vector.com> Comprehensive R Archive Network (CRAN) John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph] GPL-2 GPL-3 2024-06-12 application/tgz https://CRAN.R-project.org/package=vtreat doi:10.32614/CRAN.package.vtreat