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.
|Depends:||R (≥ 3.5.0), mlr3 (≥ 0.13.0)|
|Imports:||checkmate, R6 (≥ 2.4.1), data.table (≥ 1.13.6), paradox, mlr3measures, mlr3misc, mlr3pipelines, ggplot2|
|Suggests:||mlr3viz, rmarkdown, knitr, rpart, testthat (≥ 3.0.0), patchwork, ranger, mlr3learners, linprog, posterdown, kableExtra, fairml, iml|
|Author:||Florian Pfisterer [cre, aut], Wei Siyi [aut], Michel Lang [aut]|
|Maintainer:||Florian Pfisterer <pfistererf at googlemail.com>|
|CRAN checks:||mlr3fairness results|
|Windows binaries:||r-devel: mlr3fairness_0.3.0.zip, r-release: mlr3fairness_0.3.0.zip, r-oldrel: mlr3fairness_0.3.0.zip|
|macOS binaries:||r-release (arm64): mlr3fairness_0.3.0.tgz, r-oldrel (arm64): mlr3fairness_0.3.0.tgz, r-release (x86_64): mlr3fairness_0.3.0.tgz, r-oldrel (x86_64): mlr3fairness_0.3.0.tgz|
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