Package: fairml
Type: Package
Title: Fair Models in Machine Learning
Version: 0.8
Date: 2023-05-13
Depends: R (>= 3.5.0)
Imports: methods, glmnet
Suggests: lattice, gridExtra, parallel, cccp, CVXR, survival
Author: Marco Scutari [aut, cre]
Maintainer: Marco Scutari <scutari@bnlearn.com>
Description: 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.
License: MIT + file LICENSE
LazyData: yes
NeedsCompilation: no
Packaged: 2023-05-13 20:59:37 UTC; fizban
Repository: CRAN
Date/Publication: 2023-05-13 22:40:02 UTC
Built: R 4.2.0; ; 2023-05-17 11:08:23 UTC; unix
