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Fair machine learning regression models which take sensitive attributes into account in model estimation. Currently implementing Komiyama et al. (2018) <http://proceedings.mlr.press/v80/komiyama18a/komiyama18a.pdf>, Zafar et al. (2019) <https://www.jmlr.org/papers/volume20/18-262/18-262.pdf> and my own approach from Scutari, Panero and Proissl (2022) <https://link.springer.com/content/pdf/10.1007/s11222-022-10143-w.pdf> that uses ridge regression to enforce fairness.
Package details |
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Author | Marco Scutari [aut, cre] |
Maintainer | Marco Scutari <scutari@bnlearn.com> |
License | MIT + file LICENSE |
Version | 0.8 |
Package repository | View on CRAN |
Installation |
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