CRAN/E | logiBin

logiBin

Binning Variables to Use in Logistic Regression

Installation

About

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.

Key Metrics

Version 0.3
Published 2018-05-21 2170 days ago
Needs compilation? no
License GPL-2
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Maintainer

Maintainer

Sneha Tody

sn.tody1@gmail.com

Authors

Sneha Tody

Material

Reference manual
Package source

Vignettes

Binning variables before running logistic regression

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

logiBin archive

Imports

partykit
doParallel
data.table
foreach
iterators
parallel
stats

Suggests

knitr
rmarkdown