Identifying optimal weights to improve prediction accuracy in machine learning techniques
US11443235B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 14, 2019 |
| Grant date | Sep 13, 2022 |
| Priority date | — |
| Expiry date | Jan 24, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method, system and computer program product for improving prediction accuracy in machine learning techniques. A teacher model is constructed, where the teacher model generates a weight for each data case. The current student model is then trained using training data and the weights generated by the teacher model. After training the current student model, the current student model generates state features, which are used by the teacher model to generate new weights. A candidate student model is then trained using training data and these new weights. A reward is generated by comparing the current student model with the candidate student model using training and testing data, which is used to update the teacher model if a stopping rule has not been satisfied. Upon a stopping rule being satisfied, the weights generated by the teacher model are deemed to be the “optimal” weights which are returned to the user.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.