Machine learning method and apparatus using steps feature selection based on genetic algorithm
US11875878B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Nov 8, 2021 |
| Grant date | Jan 16, 2024 |
| Priority date | — |
| Expiry date | Nov 8, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16B5/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to a machine learning method and apparatus using steps feature selection based on a genetic algorithm, and the machine learning method includes defining a feature set including a plurality of features, generating a plurality of feature combinations including n-dimensional features (n is a natural number) for the feature set, independently constructing feature models for the plurality of feature combinations and calculating prediction accuracy for each of the feature models as a prediction result for a predetermined data set, arranging the feature models according to the prediction accuracy to determine at least one good feature model that satisfies a preset criterion, determining at least one good feature from among features included in a corresponding feature set of the at least one good feature model, and updating the feature set to include only the at least one good feature and re-determining a good feature model for a (n+1)-dimensional feature combination based on the updated feature set.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.