OptimalBinningWoE: Optimal Binning and Weight of Evidence Framework for Modeling

High-performance implementation of 37 optimal binning algorithms (16 categorical, 21 numerical) for Weight of Evidence ('WoE') transformation, credit scoring, and risk modeling. Includes advanced methods such as Mixed Integer Linear Programming ('MILP'), Genetic Algorithms, Simulated Annealing, and Monotonic Regression. Features automatic method selection based on Information Value ('IV') maximization, strict monotonicity enforcement, and efficient handling of large datasets via 'Rcpp'. Provides automated variable screening by Information Value strength and bin ordering, and generation of the equivalent 'SQL' 'CASE' expressions for in-database scoring. Fully integrated with the 'tidymodels' ecosystem for building robust machine learning pipelines. Based on methods described in Siddiqi (2006) <doi:10.1002/9781119201731> and Navas-Palencia (2020) <doi:10.48550/arXiv.2001.08025>.

Version:	1.13.3
Depends:	R (≥ 4.1.0)
Imports:	Rcpp, recipes, rlang, tibble, dials, stats, utils, graphics
LinkingTo:	Rcpp, RcppEigen, RcppNumerical
Suggests:	testthat (≥ 3.0.0), data.table, openxlsx, glmnet, generics, knitr, rmarkdown, tidymodels, workflows, parsnip, tune
Published:	2026-08-23
DOI:	10.32614/CRAN.package.OptimalBinningWoE
Author:	José Evandeilton Lopes [aut, cre, cph]
Maintainer:	José Evandeilton Lopes <evandeilton at gmail.com>
BugReports:	https://github.com/evandeilton/OptimalBinningWoE/issues
License:	MIT + file LICENSE
URL:	https://github.com/evandeilton/OptimalBinningWoE, https://evandeilton.github.io/OptimalBinningWoE/
NeedsCompilation:	yes
SystemRequirements:	C++17
Language:	en-US
Materials:	README, NEWS
CRAN checks:	OptimalBinningWoE results [issues need fixing before 2026-09-13]

Documentation:

Reference manual:	OptimalBinningWoE.html , OptimalBinningWoE.pdf
Vignettes:	Algorithm Reference: the 37 Binning Engines (source, R code) An Industrial Scorecard Pipeline (source, R code) Optimal Binning and Weight of Evidence: A Practical Guide (source, R code)

Downloads:

Package source:	OptimalBinningWoE_1.13.3.tar.gz
Windows binaries:	r-devel: OptimalBinningWoE_1.0.8.zip, r-release: OptimalBinningWoE_1.0.8.zip, r-oldrel: OptimalBinningWoE_1.13.3.zip
macOS binaries:	r-release (arm64): OptimalBinningWoE_1.0.8.tgz, r-oldrel (arm64): OptimalBinningWoE_1.0.8.tgz, r-release (x86_64): OptimalBinningWoE_1.13.3.tgz, r-oldrel (x86_64): OptimalBinningWoE_1.13.3.tgz
Old sources:	OptimalBinningWoE archive

Linking:

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