- 专利标题: System, method, and computer program product for multi-domain ensemble learning based on multivariate time sequence data
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申请号: US18268465申请日: 2022-10-20
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公开(公告)号: US12118448B2公开(公告)日: 2024-10-15
- 发明人: Linyun He , Shubham Agrawal , Yu-San Lin , Yuhang Wu , Ishita Bindlish , Chiranjeet Chetia , Fei Wang
- 申请人: Visa International Service Association
- 申请人地址: US CA San Francisco
- 专利权人: Visa International Service Association
- 当前专利权人: Visa International Service Association
- 当前专利权人地址: US CA San Francisco
- 代理机构: The Webb Law Firm
- 国际申请: PCT/US2022/047225 2022.10.20
- 国际公布: WO2023/069584A 2023.04.27
- 进入国家日期: 2023-06-20
- 主分类号: G06N20/20
- IPC分类号: G06N20/20 ; G06N5/04
摘要:
Systems, methods, and computer program products for multi-domain ensemble learning based on multivariate time sequence data are provided. A method may include receiving multivariate sequence data. At least a portion of the multivariate sequence data may be inputted into a plurality of anomaly detection models to generate a plurality of scores. The multivariate sequence data may be combined with the plurality of scores to generate combined intermediate data. The combined intermediate data may be inputted into a combined ensemble model to generate an output score. In response to determining that the output score satisfies a threshold, at least one of an alert may be communicated to a user device, the multivariate sequence data may be inputted into the feature-domain ensemble model to generate a feature importance vector, or at least one of a model-domain, a time-domain, a feature-domain, or the combined ensemble model may be updated.
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