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) .


Reference manual

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0.3 by Sneha Tody, 3 years ago

Browse source code at

Authors: Sneha Tody

Documentation:   PDF Manual  

GPL-2 license

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

Suggests knitr, rmarkdown

See at CRAN