SYSTEMS AND METHODS FOR SELECTING MACHINE LEARNING TRAINING DATA

Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of trainin...

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Bibliographic Details
Main Authors Erenrich, Daniel, Elkherj, Matthew
Format Patent
LanguageEnglish
Published 15.11.2018
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of training examples may be selected to increase efficiency between the user and the processing system by selecting the number of training examples to minimize user downtime in the machine learning process.
Bibliography:Application Number: US201816027161