fairml-package | Fair models in machine learning |
all.equal.fair.model | Extract information from fair.model objects |
coef.fair.model | Extract information from fair.model objects |
communities.and.crime | iCommunities and Crime Data Set |
compas | Criminal Offenders Screened in Florida |
cv.folds | Cross-Validation for Fair Models |
cv.loss | Cross-Validation for Fair Models |
cv.unfairness | Cross-Validation for Fair Models |
deviance.nclm | Extract information from fair.model objects |
fairml | Fair models in machine learning |
fairml.cv | Cross-Validation for Fair Models |
fairness.profile.plot | Profile Fair Models with Respect to Tuning Parameters |
fitted.fair.model | Extract information from fair.model objects |
frrm | Fair Ridge Regression Model |
german.credit | German Credit Data |
law.school.admissions | Law School Admission Council data |
methods for fair.model objects | Extract information from fair.model objects |
national.longitudinal.survey | Income and Labour Market Activities |
nclm | Nonconvex Optimization for Regression with Fairness Constraints |
nobs.fair.model | Extract information from fair.model objects |
plot.fair.model | Extract information from fair.model objects |
predict.nclm | Extract information from fair.model objects |
print.fair.model | Extract information from fair.model objects |
residuals.fair.model | Extract information from fair.model objects |
sigma.fair.model | Extract information from fair.model objects |
summary.fair.model | Extract information from fair.model objects |
summary.nclm | Extract information from fair.model objects |
vur.test | Synthetic data set to test fair regression models |