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fairml (version 0.6.1)

Fair Models in Machine Learning

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 that uses ridge regression to enforce fairness.

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Version

Install

install.packages('fairml')

Monthly Downloads

460

Version

0.6.1

License

MIT + file LICENSE

Maintainer

Marco Scutari

Last Published

January 24th, 2022

Functions in fairml (0.6.1)

law.school.admissions

Law School Admission Council data
compas

Criminal Offenders Screened in Florida
communities.and.crime

Communities and Crime Data Set
german.credit

German Credit Data
fairml.cv

Cross-Validation for Fair Models
fairml-package

Fair models in machine learning
bank

Bank Marketing
adult

Census Income
frrm

Fair Ridge Regression Model
nclm

Nonconvex Optimization for Regression with Fairness Constraints
fairness.profile.plot

Profile Fair Models with Respect to Tuning Parameters
synthetic data sets

Synthetic data sets to test fair models
national.longitudinal.survey

Income and Labour Market Activities
methods for fair.model objects

Extract information from fair.model objects
zlm

Zafar's Linear and Logistic Regressions