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) .


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install.packages("logiBin")

0.3 by Sneha Tody, a year ago


Browse source code at https://github.com/cran/logiBin


Authors: Sneha Tody


Documentation:   PDF Manual  


GPL-2 license


Imports partykit, doParallel, data.table, foreach, iterators, parallel, stats

Suggests knitr, rmarkdown


See at CRAN