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) <https://ieeexplore.ieee.org/document/6413831/>.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Suggests: caret, stats
Published: 2021-07-28
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 gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: predfairness results

Documentation:

Reference manual: predfairness.pdf

Downloads:

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

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