- 专利标题: Bias mitigating machine learning training system with multi-class target
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申请号: US18208455申请日: 2023-06-12
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公开(公告)号: US11922311B2公开(公告)日: 2024-03-05
- 发明人: Xinmin Wu , Ricky Dee Tharrington, Jr. , Ralph Walter Abbey
- 申请人: SAS Institute Inc.
- 申请人地址: US NC Cary
- 专利权人: SAS Institute Inc.
- 当前专利权人: SAS Institute Inc.
- 当前专利权人地址: US NC Cary
- 代理机构: Bell & Manning, LLC
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06N20/00
摘要:
A computing device trains a fair prediction model. A prediction model is trained and executed with observation vectors. A weight value is computed for each observation vector based on whether the predicted target variable value of a respective observation vector of the plurality of observation vectors has a predefined target event value. An observation vector is relabeled based on the computed weight value. The prediction model is retrained with each observation vector weighted by a respective computed weight value and with the target variable value of any observation vector that was relabeled. The retrained prediction model is executed. A conditional moments matrix is computed. A constraint violation matrix is computed. Computing the weight value through computing the constraint violation matrix is repeated until a stop criterion indicates retraining of the prediction model is complete. The retrained prediction model is output.
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