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fairml
View on CRAN: Click
here
Download and install fairml package within the R console
Install from CRAN:
install.packages("fairml")
Install from Github:
library("remotes")
install_github("cran/fairml") Install by package version:
library("remotes")
install_version("fairml", "0.9") Attach the package and use:
library("fairml")
Maintained by
Marco Scutari
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-08-06
Latest Update: 2025-04-29
Description:
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.
How to cite:
Marco Scutari (2020). fairml: Fair Models in Machine Learning. R package version 0.9, https://cran.r-project.org/web/packages/fairml. Accessed 15 Jul. 2026.
Previous versions and publish date:
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Other R packages that fairml depends,
imports, suggests or enhances
Complete documentation for fairml
Functions, R codes and Examples using
the fairml R package
Some associated functions: adult . bank . communities.and.crime . compas . drug.consumption . fairml-package . fairml.cv . fairness.profile.plot . flchain . frrm . german.credit . health.retirement . law.school.admissions . methods . national.longitudinal.survey . nclm . obesity.levels . synthetic . zlm .
Some associated R codes: comparisons.R . crossvalidation.R . diagnostic-plots.R . fgrrm.R . frrm.R . getters.R . glmnet.R . globals.R . nclm.R . optisolve.R . parallel.R . predict.R . preprocessing.R . print.R . profile-plots.R . sanitization-arguments.R . sanitization-cv.R . sanitization-data.R . sanitization-misc.R . sanitization-types.R . summary.R . two-stage-regression.R . utils.R . zlm.R . zlrm.R . Full fairml package functions and examples
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