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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "fairml" in publications use:'
type: software
license: MIT
title: 'fairml: Fair Models in Machine Learning'
version: 0.9.1
doi: 10.32614/CRAN.package.fairml
abstract: 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://doi.org/10.1007/s11222-022-10143-w>
  that uses ridge regression to enforce fairness.
authors:
- family-names: Scutari
  given-names: Marco
  email: scutari@bnlearn.com
repository: https://scutari.r-universe.dev
commit: 9f4156f9208a4df1878da550dfd79f275069f59a
date-released: '2026-03-07'
contact:
- family-names: Scutari
  given-names: Marco
  email: scutari@bnlearn.com