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fairml  

Fair Models in Machine Learning
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]
First Published: 2020-08-06
Latest Update: 2023-05-13
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 07 May. 2025.
Previous versions and publish date:
0.2 (2020-08-06 16:10), 0.3 (2020-09-09 17:00), 0.4 (2021-04-15 20:10), 0.5 (2021-06-16 06:10), 0.6.1 (2022-01-24 22:22), 0.6.2 (2022-04-14 12:12), 0.6.3 (2022-05-09 20:20), 0.6 (2021-08-09 18:50), 0.7 (2022-09-10 18:22), 0.8 (2023-05-14 00:40)
Other packages that cited fairml R package
View fairml citation profile
Other R packages that fairml depends, imports, suggests or enhances
Complete documentation for fairml
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