- 专利标题: Machine learning model feature contribution analytic system
-
申请号: US16451228申请日: 2019-06-25
-
公开(公告)号: US10510022B1公开(公告)日: 2019-12-17
- 发明人: Ricky Dee Tharrington, Jr. , Xin Jiang Hunt , 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: G06N20/00
- IPC分类号: G06N20/00 ; G06N5/04 ; G06F17/16 ; G06F16/245
摘要:
Systems and methods for machine learning, models, and related explainability and interpretability are provided. A computing device determines a contribution of a feature to a predicted value. A feature computation dataset is defined based on a selected next selection vector. A prediction value is computed for each observation vector included in the feature computation dataset using a trained predictive model. An expected value is computed for the selected next selection vector based on the prediction values. The feature computation dataset is at least a partial copy of a training dataset with each variable value replaced in each observation vector included in the feature computation dataset based on the selected next selection vector. Each replaced variable value is replaced with a value included in a predefined query for a respective variable. A Shapley estimate value is computed for each variable.
信息查询