Package: woeBinning 0.1.6

Thilo Eichenberg

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

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.

Authors:Thilo Eichenberg

woeBinning_0.1.6.tar.gz
woeBinning_0.1.6.tar.gz(r-4.5-noble)woeBinning_0.1.6.tar.gz(r-4.4-noble)
woeBinning_0.1.6.tgz(r-4.4-emscripten)woeBinning_0.1.6.tgz(r-4.3-emscripten)
woeBinning.pdf |woeBinning.html
woeBinning/json (API)

# Install 'woeBinning' in R:
install.packages('woeBinning', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

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This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.15 score 5 stars 28 scripts 719 downloads 5 exports 0 dependencies

Last updated 6 years agofrom:a75966e200. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 04 2024
R-4.5-linuxOKDec 04 2024

Exports:woe.binningwoe.binning.deploywoe.binning.plotwoe.binning.tablewoe.tree.binning

Dependencies: