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    Cumulative incrementality scores for evaluating the performance of machine learning models
    1.
    发明授权
    Cumulative incrementality scores for evaluating the performance of machine learning models 有权

    公开(公告)号：US11972464B2

    公开(公告)日：2024-04-30

    申请号：US17752800

    申请日：2022-05-24

    Applicant: Maplebear Inc.

    Inventor： Daniel Summerhays ,  Ramasubramanian Balasubramanian

    IPC: G06Q30/0601 ,  G06N5/022

    CPC classification number: G06Q30/0601 ,  G06N5/022

    Abstract: An online concierge system uses a cumulative incrementality score to evaluate the performance of incrementality models used by the online concierge system to identify users for treatment. The online concierge system applies an incrementality model to a set of examples to generate predicted incrementality scores for the examples. The online concierge system ranks the examples based on the predicted incrementality scores for the examples and groups the examples based on their rankings. The online concierge system iteratively computes cumulative incrementality scores for each grouping based on the examples of each grouping, and computes a final cumulative incrementality score for the incrementality model based on each of the cumulative incrementality scores.

    CUMULATIVE INCREMENTALITY SCORES FOR EVALUATING THE PERFORMANCE OF MACHINE LEARNING MODELS
    2.
    发明公开
    CUMULATIVE INCREMENTALITY SCORES FOR EVALUATING THE PERFORMANCE OF MACHINE LEARNING MODELS 审中-公开

    公开(公告)号：US20230385886A1

    公开(公告)日：2023-11-30

    申请号：US17752800

    申请日：2022-05-24

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Daniel Summerhays ,  Ramasubramanian Balasubramanian

    IPC: G06Q30/06 ,  G06N5/02

    CPC classification number: G06Q30/0601 ,  G06N5/022

    Abstract: An online concierge system uses a cumulative incrementality score to evaluate the performance of incrementality models used by the online concierge system to identify users for treatment. The online concierge system applies an incrementality model to a set of examples to generate predicted incrementality scores for the examples. The online concierge system ranks the examples based on the predicted incrementality scores for the examples and groups the examples based on their rankings. The online concierge system iteratively computes cumulative incrementality scores for each grouping based on the examples of each grouping, and computes a final cumulative incrementality score for the incrementality model based on each of the cumulative incrementality scores.

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