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Bias detection and reduction in machine-learning techniques

Grant US12596957B2 Kind: B2 Apr 07, 2026

Assignee

EQUIFAX, INC.

Inventors

Mufeng Zou, Swathi Veeravelly, Marcus Bruhn

Abstract

In some aspects, a computing system can improve a machine learning model for risk assessment by removing or reducing bias in the machine learning model. The training process for the machine learning model can include training the machine learning model using training samples, obtaining data for a protected attribute, and calculating a bias metric using the data for the protected attribute and data obtained from the trained machine learning model. Based on the bias metric, bias associated with the machine learning model can be detected. The machine learning model can be modified based on the detected bias and re-trained. The re-trained machine learning model can be used to predict a risk indicator for a target entity. The predicted risk indicator can be transmitted to a remote computing device and be used for controlling access of the target entity to one or more interactive computing environments.

CPC Classifications

G06N 20/00 G06N 20/10 G06N 5/04 G06N 5/01 G06N 3/098 G06N 3/088 G06N 3/0454-0455 H04L 63/10 G06F 40/44 G06F 18/2155 G06F 18/2113 G06F 18/217 G06Q 10/0635

Filing Date

2022-10-14

Application No.

18046661

Claims

20