logiBin: Binning Variables to Use in Logistic Regression

Fast binning of multiple variables using parallel processing. A summary of all the variables binned is generated which provides the information value, entropy, an indicator of whether the variable follows a monotonic trend or not, etc. It supports rebinning of variables to force a monotonic trend as well as manual binning based on pre specified cuts. The cut points of the bins are based on conditional inference trees as implemented in the partykit package. The conditional inference framework is described by Hothorn T, Hornik K, Zeileis A (2006) <doi:10.1198/106186006X133933>.

Version:	0.3
Imports:	partykit, doParallel, data.table, foreach, iterators, parallel, stats
Suggests:	knitr, rmarkdown
Published:	2018-05-21
DOI:	10.32614/CRAN.package.logiBin
Author:	Sneha Tody
Maintainer:	Sneha Tody <sn.tody1 at gmail.com>
License:	GPL-2
NeedsCompilation:	no
CRAN checks:	logiBin results

Documentation:

Reference manual:	logiBin.pdf
Vignettes:	Binning variables before running logistic regression

Downloads:

Package source:	logiBin_0.3.tar.gz
Windows binaries:	r-devel: logiBin_0.3.zip, r-release: logiBin_0.3.zip, r-oldrel: logiBin_0.3.zip
macOS binaries:	r-release (arm64): logiBin_0.3.tgz, r-oldrel (arm64): logiBin_0.3.tgz, r-release (x86_64): logiBin_0.3.tgz, r-oldrel (x86_64): logiBin_0.3.tgz
Old sources:	logiBin archive

Linking:

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