CRAN/E | fairml

fairml

Fair Models in Machine Learning

Installation

About

Fair machine learning regression models which take sensitive attributes into account in model estimation. Currently implementing Komiyama et al. (2018) , Zafar et al. (2019) and my own approach from Scutari, Panero and Proissl (2022) that uses ridge regression to enforce fairness.

Key Metrics

Version 0.8
R ≥ 3.5.0
Published 2023-05-13 139 days ago
Needs compilation? no
License MIT
License File
CRAN checks fairml results

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Maintainer

Maintainer

Marco Scutari

scutari@bnlearn.com

Authors

Marco Scutari

aut / cre

Material

ChangeLog
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

fairml archive

Depends

R ≥ 3.5.0

Imports

methods
glmnet

Suggests

lattice
gridExtra
parallel
cccp
CVXR
survival

Reverse Suggests

mlr3fairness