aif360 (version 0.1.0)

prejudice_remover: Prejudice Remover

Description

Prejudice remover is an in-processing technique that adds a discrimination-aware regularization term to the learning objective

Usage

prejudice_remover(eta=1.0, sensitive_attr='',class_attr='')

Arguments

eta

fairness penalty parameter

sensitive_attr

name of protected attribute

class_attr

label name

Examples

# NOT RUN {
# An example using the Adult Dataset
load_aif360_lib()
ad <- adult_dataset()
model <- prejudice_remover(class_attr = "income-per-year", sensitive_attr = "race")
model$fit(ad)
ad_pred <- model$predict(ad)
# }