INCREMENTAL TRAINING FOR REAL-TIME MODEL PREFORMANCE ENHANCEMENT

Methods, systems, and computer-readable storage media for receiving IRF data sets, the IRF data sets including a set of records including inference results determined by the ML model during production use of the ML model and at least one correction to an inference result, executing incremental train...

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Bibliographic Details
Main Authors Arumugam, Rajesh Vellore, Baur, Stefan Klaus, Soegeng, Andrew Ivan
Format Patent
LanguageEnglish
Published 27.04.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:Methods, systems, and computer-readable storage media for receiving IRF data sets, the IRF data sets including a set of records including inference results determined by the ML model during production use of the ML model and at least one correction to an inference result, executing incremental training of the ML model to provide an updated ML model by selectively filtering one or more records of the set of records to adjust a negative sample to positive sample proportion of a sub-set of records based on a negative sample to positive sample proportion of initial training of the ML model, for each record in the sub-set of records, determining a weight, and during incremental training, applying the weight of a respective record being in a loss function in determining an accuracy of the ML model based on the respective record, and deploying the updated ML model for production use.
Bibliography:Application Number: US202117452441