Machine-learning models to leverage behavior-dependent processes

Provided is a process, including: obtaining a first training dataset of subject-entity records; training a first machine-learning model on the first training dataset; forming virtual subject-entity records by appending members of a set of candidate action sequences to time-series of at least some of...

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Bibliographic Details
Main Authors Prakash, Arun, Klose, Gregory, Kraemer, Andrew, Briançon, Alain, Wegan, Michael, Silberman, Gabriel M, Harper, Lee
Format Patent
LanguageEnglish
Published 27.12.2022
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:Provided is a process, including: obtaining a first training dataset of subject-entity records; training a first machine-learning model on the first training dataset; forming virtual subject-entity records by appending members of a set of candidate action sequences to time-series of at least some of the subject-entity records; forming a second training dataset by labeling the virtual subject-entity records with predictions of the first machine-learning model; and training a second machine-learning model on the second training dataset.
Bibliography:Application Number: US201916408404