fairml: Fair Models in Machine Learning

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

AuthorMarco Scutari [aut, cre]
MaintainerMarco Scutari <scutari@bnlearn.com>
LicenseMIT + file LICENSE
Version0.8
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("fairml")

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fairml documentation built on May 31, 2023, 6:02 p.m.