发明授权
- 专利标题: Generic workflow for classification of highly imbalanced datasets using deep learning
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申请号: US16718524申请日: 2019-12-18
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公开(公告)号: US11416748B2公开(公告)日: 2022-08-16
- 发明人: Ajinkya Patil , Waqas Ahmad Farooqi , Jochim Fibich , Eckehard Schmidt , Michael Jaehnisch
- 申请人: SAP SE
- 申请人地址: DE Walldorf
- 专利权人: SAP SE
- 当前专利权人: SAP SE
- 当前专利权人地址: DE Walldorf
- 代理机构: Fish & Richardson P.C.
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06N3/04
摘要:
Methods, systems, and computer-readable storage media for providing a binary classifier include receiving a biased dataset, the biased data set including a plurality of records, each record being assigned to a class of a plurality of classes, one class including a majority class, performing data engineering on at least a portion of the biased dataset to provide a revised dataset, providing a trained deep autoencoder (DAE) by training a DAE using only records assigned to the majority class from the revised dataset, the trained DAE including a binary classifier that classifies records into one of the majority class and a minority class, validating the trained DAE using validation data that is based on at least a portion of the biased dataset, and providing the trained DAE for production use within a production system.
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