Systems and methods for hyper parameter optimization for improved machine learning ensembles
US11580325B2 · kind B2 · utility
2Cited by
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Key dates
| Filing date | Jan 25, 2019 |
| Grant date | Feb 14, 2023 |
| Priority date | — |
| Expiry date | Dec 17, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
One or more computing devices, systems, and/or methods for hyper parameter optimization for machine learning ensemble generation are provided. For example, one or more base models are trained using diverse sets of hyper parameters, wherein different sets of hyper parameters (e.g., hyper parameters with different values) are used to train different base models. A matrix, populated with predictions from the set of base models, is generated. A machine learning ensemble is generated by processing the matrix utilizing a meta learner.
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