Invention Grant
- Patent Title: Concurrent binning of machine learning data
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Application No.: US14489449Application Date: 2014-09-17
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Publication No.: US09672474B2Publication Date: 2017-06-06
- Inventor: Leo Parker Dirac , Michael Brueckner , Ralf Herbrich
- Applicant: Amazon Technologies, Inc.
- Applicant Address: US NV Reno
- Assignee: Amazon Technologies, Inc.
- Current Assignee: Amazon Technologies, Inc.
- Current Assignee Address: US NV Reno
- Agency: Meyertons, Hood, Kivlin, Kowert & Goetzel, P.C.
- Agent Robert C. Kowert
- Main IPC: G06F15/18
- IPC: G06F15/18 ; G06N99/00

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.
Public/Granted literature
- US20150379428A1 CONCURRENT BINNING OF MACHINE LEARNING DATA Public/Granted day:2015-12-31
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