A Fair Classifier Using Kernel Density Estimation

no code implementations • NeurIPS 2020 • Jaewoong Cho, Gyeongjo Hwang, Changho Suh

As machine learning becomes prevalent in a widening array of sensitive applications such as job hiring and criminal justice, one critical aspect that machine learning classifiers should respect is to ensure fairness: guaranteeing the irrelevancy of a prediction output to sensitive attributes such as gender and race.

BIG-bench Machine Learning Binary Classification +2