woeBinning: Supervised Weight of Evidence Binning of Numeric Variables and Factors
Version 0.1.4

Implements an automated binning of numeric variables and factors with respect to a dichotomous target variable. Two approaches are provided: An implementation of fine and coarse classing that merges granular classes and levels step by step. And a tree-like approach that iteratively segments the initial bins via binary splits. Both procedures merge, respectively split, bins based on similar weight of evidence (WOE) values and stop via an information value (IV) based criteria. The package can be used with single variables or an entire data frame. It provides flexible tools for exploring different binning solutions and for deploying them to (new) data.

Getting started

Package details

AuthorThilo Eichenberg
Date of publication2017-06-12 11:30:15 UTC
MaintainerThilo Eichenberg <[email protected]>
LicenseGPL (>= 2)
Version0.1.4
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("woeBinning")

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woeBinning documentation built on June 20, 2017, 9:12 a.m.