prejudice_remover: Prejudice Remover

In aif360: Help Detect and Mitigate Bias in Machine Learning Models

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

# 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)

aif360 documentation built on July 1, 2020, 5:34 p.m.