Package: OptimalBinningWoE
Type: Package
Title: Optimal Binning and Weight of Evidence Framework for Modeling
Version: 1.14.1
Date: 2026-09-30
Authors@R: 
    person(given = "José Evandeilton",
           family = "Lopes",
           role = c("aut", "cre", "cph"),
           email = "evandeilton@gmail.com",
           comment = c(ORCID = "0009-0007-5887-4084"))
Description: High-performance implementation of 28 binning algorithms
        (37 implementations: 21 numerical, 16 categorical) for Weight
        of Evidence ('WoE') transformation, credit scoring, and risk
        modeling. Methods include dynamic programming over ordered
        levels, entropy-based ('MDLP') and chi-square ('ChiMerge')
        partitioning, isotonic regression, simulated annealing,
        kernel-density binning, sketch-based binning (KLL and
        Count-Min), and greedy merging heuristics. Features a default
        algorithm chosen from the target type, monotonicity enforcement
        where the algorithm supports it, 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>.
License: MIT + file LICENSE
URL: https://github.com/evandeilton/OptimalBinningWoE,
        https://evandeilton.github.io/OptimalBinningWoE/
BugReports: https://github.com/evandeilton/OptimalBinningWoE/issues
Depends: R (>= 4.1.0)
Encoding: UTF-8
Language: en-US
Imports: Rcpp, recipes, rlang, tibble, dials, stats, utils, graphics
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), data.table, openxlsx, glmnet, generics,
        knitr, rmarkdown, tidymodels, workflows, parsnip, tune
Config/testthat/edition: 3
SystemRequirements: C++17
VignetteBuilder: knitr
Config/roxygen2/version: 8.0.0
Config/pak/sysreqs: libicu-dev
Repository: https://evandeilton.r-universe.dev
Date/Publication: 2026-10-15 22:31:45 UTC
RemoteUrl: https://github.com/evandeilton/optimalbinningwoe
RemoteRef: HEAD
RemoteSha: e5a17f34b20419d0de8bfedce011461fed7ed1eb
NeedsCompilation: yes
Packaged: 2026-10-15 23:27:14 UTC; root
Author: José Evandeilton Lopes [aut, cre, cph] (ORCID:
    <https://orcid.org/0009-0007-5887-4084>)
Maintainer: José Evandeilton Lopes <evandeilton@gmail.com>