Invention Grant
- Patent Title: Detection of machine learning model degradation
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Application No.: US16567695Application Date: 2019-09-11
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Publication No.: US11625602B2Publication Date: 2023-04-11
- Inventor: Siar Sarferaz
- Applicant: SAP SE
- Applicant Address: DE Walldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Walldorf
- Agency: Mintz Levin Cohn Ferris Glovsky and Popeo, P.C.
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N20/20 ; G06N3/084

Abstract:
A method may include training, based on a first training dataset, a machine learning model. A degradation of the machine learning model may be detected based on one or more accuracy key performance indicators including a prediction power metric and a prediction confidence metric. The degradation of the machine learning model may also be detected based on a drift and skew in an input dataset and/or an output dataset of the machine learning model. Furthermore, the degradation of the machine learning model may be detected based on an explicit feedback and/or an implicit feedback on a performance of the machine learning model. In response to detecting the degradation of the machine learning model, the machine learning model may be retrained based on a second training dataset that includes at least one training sample not included in the first training dataset. Related systems and articles of manufacture are also provided.
Public/Granted literature
- US20210073627A1 DETECTION OF MACHINE LEARNING MODEL DEGRADATION Public/Granted day:2021-03-11
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