Disparate Impact Remover

Disparate impact remover is a preprocessing technique that edits feature values increase group fairness while preserving rank-ordering within groups

Usage

disparate_impact_remover(repair_level = 1.0, sensitive_attribute = '')

Arguments

repair_level

Repair amount. 0.0 is no repair while 1.0 is full repair.

sensitive_attribute

Single protected attribute with which to do repair.

Examples

if (FALSE) {
# 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)
}