Concurrent binning of machine learning data

    公开(公告)号:US09672474B2

    公开(公告)日:2017-06-06

    申请号:US14489449

    申请日:2014-09-17

    CPC classification number: G06N99/005

    Abstract: Variables of observation records to be used to generate a machine learning model are identified as candidates for quantile binning transformations. In accordance with a particular concurrent binning plan generated for a particular variable, a plurality of quantile binning transformations are applied to the particular variable, including a first transformation with a first bin count and a second transformation with a different bin count. The first and second transformations result in the inclusion of respective parameters or weights for binned features in a parameter vector of the model. In a post-training phase run of the model, at least one parameter corresponding to a binned feature is used to generate a prediction.

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