doi:10.1007/s10115-011-0463-8> and "Equalized Odds" described in 'Hardt et al.' (2016) <https://papers.nips.cc/paper/2016/file/9d2682367c3935defcb1f9e247a97c0d-Paper.pdf>. Integration with 'mlr3' allows for auditing of ML models as well as convenient joint tuning of machine learning algorithms and debiasing methods.">

mlr3fairness: Fairness Auditing and Debiasing for 'mlr3' (original) (raw)

Integrates fairness auditing and bias mitigation methods for the 'mlr3' ecosystem. This includes fairness metrics, reporting tools, visualizations and bias mitigation techniques such as "Reweighing" described in 'Kamiran, Calders' (2012) <doi:10.1007/s10115-011-0463-8> and "Equalized Odds" described in 'Hardt et al.' (2016) <https://papers.nips.cc/paper/2016/file/9d2682367c3935defcb1f9e247a97c0d-Paper.pdf>. Integration with 'mlr3' allows for auditing of ML models as well as convenient joint tuning of machine learning algorithms and debiasing methods.

Version: 0.4.0
Depends: R (≥ 3.4.0)
Imports: checkmate, data.table (≥ 1.13.6), ggplot2, mlr3 (≥ 0.23.0.9000), mlr3learners, mlr3measures, mlr3misc, mlr3pipelines, paradox, R6 (≥ 2.4.1), rlang
Suggests: cccp, CVXR, pagedown, fairml, future, iml, kableExtra, knitr, linprog, lgr, mlr3viz, patchwork, ranger, rmarkdown, rpart, testthat (≥ 3.1.0)
Published: 2025-06-24
DOI: 10.32614/CRAN.package.mlr3fairness
Author: Florian Pfisterer ORCID iD [cre, aut], Wei Siyi [aut], Michel Lang ORCID iD [aut]
Maintainer: Florian Pfisterer
BugReports: https://github.com/mlr-org/mlr3fairness/issues
License: LGPL-3
URL: https://mlr3fairness.mlr-org.com,https://github.com/mlr-org/mlr3fairness
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: mlr3fairness results

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