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.1173314.

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Description file content

Package
vtreat
Type
Package
Title
A Statistically Sound 'data.frame' Processor/Conditioner
Version
1.3.1
Date
2018-09-10
URL
BugReports
https://github.com/WinVector/vtreat/issues
Maintainer
John Mount
Description
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.
License
GPL-3
Depends
R (>= 3.2.1)
Imports
stats, parallel, wrapr (>= 1.6.1)
Suggests
rquery (>= 0.6.2), rqdatatable (>= 0.1.4), testthat, knitr, rmarkdown, data.table (>= 1.11.4), ggplot2, DBI, RSQLite, datasets
LazyData
true
VignetteBuilder
knitr
RoxygenNote
6.1.0
ByteCompile
true
NeedsCompilation
no
Packaged
2018-09-10 14:42:58 UTC; johnmount
Author
John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Repository
CRAN
Date/Publication
2018-09-10 16:00:02 UTC

install.packages('vtreat')

1.3.1

14 days ago

https://github.com/WinVector/vtreat/

John Mount

GPL-3

Depends on

R (>= 3.2.1)

Imports

stats, parallel, wrapr (>= 1.6.1)

Suggests

rquery (>= 0.6.2), rqdatatable (>= 0.1.4), testthat, knitr, rmarkdown, data.table (>= 1.11.4), ggplot2, DBI, RSQLite, datasets

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