predfairness: Discrimination Mitigation for Machine Learning Models

Based on different statistical definitions of discrimination, several methods have been proposed to detect and mitigate social inequality in machine learning models. This package aims to provide an alternative to fairness treatment in predictive models. The ROC method implemented in this package is described by Kamiran, Karim and Zhang (2012) <>.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Suggests: caret, stats
Published: 2021-07-28
DOI: 10.32614/CRAN.package.predfairness
Author: Thaís de Bessa Gontijo de Oliveira [aut, cre], Leonardo Paes Vieira [aut], Gustavo Rodrigues Lacerda Silva [ctb], Barbara Bianca Alves Cardoso [ctb], Douglas Alexandre Gomes Vieira [ctb]
Maintainer: Thaís de Bessa Gontijo de Oliveira <thais.bgo at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: predfairness results


Reference manual: predfairness.pdf


Package source: predfairness_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): predfairness_0.1.0.tgz, r-oldrel (arm64): predfairness_0.1.0.tgz, r-release (x86_64): predfairness_0.1.0.tgz, r-oldrel (x86_64): predfairness_0.1.0.tgz


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