Hierarchical tournament-based machine learning predictions
US11748640B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 2, 2022 |
| Grant date | Sep 5, 2023 |
| Priority date | — |
| Expiry date | Nov 2, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/022
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and techniques for hierarchical tournament-based machine learning predictions are described herein. A machine learning selection model may be trained with training data. A configuration may be received that includes the metric and a target prediction. A set of evaluation component combinations may be selected using the machine learning selection model. Each evaluation component combination of the set of evaluation component combinations may include an algorithm, a hierarchical learning model corresponding to a level of a hierarchy, and a prediction model for the target prediction. The set of evaluation component combinations may be transmitted to a cluster of computing nodes. Output results may be received for the set of evaluation component combinations. The output results may be evaluated using the metric to determine a winning evaluation component combination. The winning evaluation component combination may be stored in storage for use in calculating future predictions for the target prediction.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.