woeR: Weight of Evidence Based Segmentation of a Variable

Segment a numeric variable based on a dichotomous dependent variable by using the weight of evidence (WOE) approach (Ref: Siddiqi, N. (2006) <doi:10.1002/9781119201731.biblio>). The underlying algorithm adopts a recursive approach to create segments that are diverse in respect of their WOE values and meet the demands of user-defined parameters. The algorithm also aims to maintain a monotonic trend in WOE values of consecutive segments. As such, it can be particularly helpful in improving robustness of linear and logistic regression models.

Version: 0.2.1
Depends: R (≥ 3.4.0)
Imports: dplyr
Suggests: smbinning
Published: 2019-01-23
Author: Kashish Soien
Maintainer: Kashish Soien <kashish.soien19 at gmail.com>
BugReports: https://github.com/kraken19/woeR/issues
License: GPL-3
NeedsCompilation: no
CRAN checks: woeR results


Reference manual: woeR.pdf
Package source: woeR_0.2.1.tar.gz
Windows binaries: r-devel: woeR_0.2.1.zip, r-release: woeR_0.2.1.zip, r-oldrel: woeR_0.2.1.zip
macOS binaries: r-release: woeR_0.2.1.tgz, r-oldrel: woeR_0.2.1.tgz
Old sources: woeR archive


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