公开(公告)号：US11610079B2

公开(公告)日：2023-03-21

申请号：US16777912

申请日：2020-01-31

Applicant: salesforce.com, inc.

Inventor： Michael Yang

IPC: G06K9/62 ,  G06N20/00

Abstract: There is provided computer implemented method for detecting and reducing or removing bias for generating a machine learning model, comprising: prior to generating the machine learning model: receiving a training dataset, comprising target inputs, each comprising parameters and labelled with a corresponding target output, wherein at least one of the parameters of at least of the target inputs comprises a sensitive parameter indicative of the corresponding target input assigned to a sensitive group that is potentially biased against other target inputs that are excluded from the sensitive group, analyzing the training dataset to identify target inputs affected by label bias when a statistically significant difference is detected between target inputs assigned to the sensitive group and target inputs excluded from the sensitive group, correcting labels of the target inputs affected by label bias, and generating the machine learning model using the corrected labels.