SYSTEMS AND METHODS FOR CLASSIFICATION AND TIME SERIES CALIBRATION IN IDENTITY HEALTH ANALYSIS

    公开(公告)号:WO2022212306A1

    公开(公告)日:2022-10-06

    申请号:PCT/US2022/022247

    申请日:2022-03-29

    Abstract: Aspects of the disclosure relate to using machine learning methods for identity health scoring. A computing platform may train a machine learning model, using historical event information, by: 1) classifying the historical event information using logical regression, and 2) after classifying the historical event information, performing time series calibration on the classified historical event information, wherein training the machine learning model configures the machine learning model to output identity health information. The computing platform may receive new event information. The computing platform may input the new event information into the machine learning model, which may cause the machine learning model to output the identity health information. The computing platform may send, to a client device, the identity health information and one or more commands directing the client device to display an identity health interface, which may cause the client device to display the identity health interface.

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