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% Generated by roxygen2: do not edit by hand | |
% Please edit documentation in R/preprocessing_disparate_impact_remover.R | |
\name{disparate_impact_remover} | |
\alias{disparate_impact_remover} | |
\title{Disparate Impact Remover} | |
\usage{ | |
disparate_impact_remover(repair_level = 1.0, sensitive_attribute = '') | |
} | |
\arguments{ | |
\item{repair_level}{Repair amount. 0.0 is no repair while 1.0 is full repair.} | |
\item{sensitive_attribute}{Single protected attribute with which to do repair.} | |
} | |
\description{ | |
Disparate impact remover is a preprocessing technique that edits feature values increase group fairness while preserving rank-ordering within groups | |
} | |
\examples{ | |
\dontrun{ | |
# An example using the Adult Dataset | |
load_aif360_lib() | |
ad <- adult_dataset() | |
p <- list("race", 1) | |
u <- list("race", 0) | |
di <- disparate_impact_remover(repair_level = 1.0, sensitive_attribute = "race") | |
rp <- di$fit_transform(ad) | |
di_2 <- disparate_impact_remover(repair_level = 0.8, sensitive_attribute = "race") | |
rp_2 <- di_2$fit_transform(ad) | |
} | |
} | |