Invention Grant
- Patent Title: Optimized training of linear machine learning models
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Application No.: US14484201Application Date: 2014-09-11
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Publication No.: US10318882B2Publication Date: 2019-06-11
- Inventor: Michael Brueckner , Daniel Blick
- 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 ; G06N20/00 ; H04L29/08 ; G06N7/00 ; G06N5/02 ; G06K9/62

Abstract:
An indication of a data source to be used to train a linear prediction model is obtained. The model is to generate predictions using respective parameters assigned to a plurality of features derived from observation records of the data source. The parameter values are stored in a parameter vector. During a particular learning iteration of the training phase of the model, one or more features for which parameters are to be added to the parameter vector are identified. In response to a triggering condition, parameters for one or more features are removed from the parameter vector based on an analysis of relative contributions of the features represented in the parameter vector to the model's predictions. After the parameters are removed, at least one parameter is added to the parameter vector.
Public/Granted literature
- US20160078361A1 OPTIMIZED TRAINING OF LINEAR MACHINE LEARNING MODELS Public/Granted day:2016-03-17
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