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optbinningR: Optimal Binning Methods for Predictive Modeling and Analytics

Native R tools for optimal binning workflows in predictive modeling. The package provides APIs for binary, multi-class and continuous targets, with multi-variable binning and scorecard workflows. Methods are informed by Navas-Palencia (2020) <doi:10.48550/arXiv.2001.08025> and Navas-Palencia (2021) <doi:10.48550/arXiv.2104.08619>.

Version: 0.2.1
Depends: R (≥ 4.1.0)
Imports: stats, utils
Suggests: testthat (≥ 3.0.0), jsonlite, lintr, covr
Published: 2026-03-16
DOI: 10.32614/CRAN.package.optbinningR
Author: S. Rani [aut, cre]
Maintainer: S. Rani <s.rani at live.com>
BugReports: https://github.com/s-rani1/optbinningR/issues
License: MIT + file LICENSE
URL: https://github.com/s-rani1/optbinningR
NeedsCompilation: no
Materials: README
CRAN checks: optbinningR results

Documentation:

Reference manual: optbinningR.html , optbinningR.pdf

Downloads:

Package source: optbinningR_0.2.1.tar.gz
Windows binaries: r-devel: optbinningR_0.2.1.zip, r-release: optbinningR_0.2.1.zip, r-oldrel: optbinningR_0.2.1.zip
macOS binaries: r-release (arm64): optbinningR_0.2.1.tgz, r-oldrel (arm64): optbinningR_0.2.1.tgz, r-release (x86_64): optbinningR_0.2.1.tgz, r-oldrel (x86_64): optbinningR_0.2.1.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.