公开(公告)号：GB2597406A

公开(公告)日：2022-01-26

申请号：GB202115858

申请日：2020-03-18

Applicant: IBM

Inventor： GEORGIOS CHALOULOS ,  FREDERIK FLOETHER ,  FLORIAN GRAF ,  PATRICK LUSTENBERGER ,  STEFAN RAVIZZA ,  ERIC SLOTTKE

IPC: G06N20/00

Abstract: A computer-implemented method for improving fairness in a supervised machine-learning model may be provided. The method comprises linking the supervised machine-learning model to a reinforcement learning meta model, selecting a list of hyper-parameters and parameters of the supervised machine-learning model, and controlling at least one aspect of the supervised machine-learning model by adjusting hyper-parameters values and parameter values of the list of hyper-parameters and parameters of the supervised machine-learning model by a reinforcement learning engine relating to the reinforcement learning meta model by calculating a reward function based on multiple conflicting objective functions. The method further comprises repeating iteratively the steps of selecting and controlling for improving a fairness value of the supervised machine-learning model.