Random feature transformation forests for automatic feature engineering
US11275974B2 · kind B2 · utility
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Key dates
| Filing date | Sep 17, 2018 |
| Grant date | Mar 15, 2022 |
| Priority date | — |
| Expiry date | Jan 14, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments for automated feature engineering by one or more processors are described. One or more selected transformations may be applied to a set of features in a dataset to create a set of transform features using random feature transformation forest (RFTF) classifiers. A transform feature may be selected from the set of transform features having a highest discriminative power as compared to other features of the set of transform features. At each node in a decision tree, store the selected feature, a split value, and the one or more selected transformations for the transform feature.
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