Parallel ensemble of machine learning algorithms
US11443244B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jun 5, 2019 |
| Grant date | Sep 13, 2022 |
| Priority date | — |
| Expiry date | Jul 14, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An aspect of the invention includes receiving machine learning (ML) training data that includes a plurality of features for a plurality of observations. The ML training data is broken into a plurality of non-overlapping subsets of features and observations. A first ML algorithm is trained based on a first subset of the features and observations, and a second ML algorithm is trained based on a second subset of the features and observations. The training of the first ML algorithm overlaps in time with the training of the second ML algorithm. The first and second ML algorithms are tested. Either the first or second ML algorithm is selected based at least in part on results of the testing. The selected ML algorithm is retained as a trained ML algorithm for predicting one or more of the plurality of features based on one or more others of the plurality of features.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.