The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Apr. 04, 2023
Filed:
Apr. 18, 2019
Oracle International Corporation, Redwood Shores, CA (US);
Hesam Fathi Moghadam, Sunnyvale, CA (US);
Sandeep Agrawal, San Jose, CA (US);
Venkatanathan Varadarajan, Austin, TX (US);
Anatoly Yakovlev, Hayward, CA (US);
Sam Idicula, Santa Clara, CA (US);
Nipun Agarwal, Saratoga, CA (US);
Oracle International Corporation, Redwood Shores, CA (US);
Abstract
Techniques are provided for selection of machine learning algorithms based on performance predictions by using hyperparameter predictors. In an embodiment, for each mini-machine learning model (MML model), a respective hyperparameter predictor set that predicts a respective set of hyperparameter settings for a data set is trained. Each MML model represents a respective reference machine learning model (RML model). Data set samples are generated from the data set. Meta-feature sets are generated, each meta-feature set describing a respective data set sample. A respective target set of hyperparameter settings are generated for said each MML model using a hypertuning algorithm. The meta-feature sets and the respective target set of hyperparameter settings are used to train the respective hyperparameter predictor set. Each hyperparameter predictor set is used during training and inference to improve the accuracy of automatically selecting a RML model per data set.