Post-hoc Bias Scoring Is Optimal For Fair Classification

arXiv:2310.05725v3 Announce Type: replace-cross
Abstract: We consider a binary classification problem under group fairness constraints, which can be one of Demographic Parity (DP), Equalized Opportunity (EOp), or Equalized Odds (EO). We propose an explicit characterization of Bayes optimal classifier under the fairness constraints, which turns out to be a simple modification rule of the unconstrained classifier. Namely, we introduce a novel instance-level measure of bias, which we call bias score, and the modification rule is a simple linear rule on …

abstract arxiv bayes bias binary classification classifier constraints cs.lg fair fairness scoring simple stat.ml type