- 专利标题: Evaluating machine learning model performance by leveraging system failures
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申请号: US18103483申请日: 2023-01-30
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公开(公告)号: US11763207B1公开(公告)日: 2023-09-19
- 发明人: Aviv Ben Arie , Omer Zalmanson
- 申请人: Intuit Inc.
- 申请人地址: US CA Mountain View
- 专利权人: Intuit Inc.
- 当前专利权人: Intuit Inc.
- 当前专利权人地址: US CA Mountain View
- 代理机构: Ferguson Braswell Fraser Kubasta PC
- 主分类号: G06N20/20
- IPC分类号: G06N20/20 ; H04L9/40
摘要:
A method including monitoring, using a machine learning model, network events of a network. The machine learning model generates fraud scores representing a corresponding probability that a corresponding network event is fraudulent. The method also includes detecting a failure of the machine learning model to generate, within a threshold time, a given fraud score for a given network event. The method also includes determining, by the machine learning model and after the threshold time, the given fraud score. The method also includes logging, responsive to detecting the failure, the given network event in a first table, including logging the given fraud score. The method also includes determining a metric based on comparing the first table to a second table which logs at least the given fraud score and the fraud scores. The method also includes generating an adjusted machine learning model based on the metric.
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