Package: fairml
Type: Package
Title: Fair Models in Machine Learning
Version: 0.6.2
Date: 2022-04-14
Depends: R (>= 3.5.0)
Imports: methods, optiSolve, CVXR, glmnet
Suggests: lattice, parallel
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 that uses ridge regression to enforce fairness.
License: MIT + file LICENSE
LazyData: yes
NeedsCompilation: no
Packaged: 2022-04-14 00:49:31 UTC; fizban
Repository: CRAN
Date/Publication: 2022-04-14 10:12:36 UTC
Built: R 4.0.5; ; 2022-04-21 15:09:39 UTC; windows
