Dynamic accuracy-based deployment and monitoring of machine learning models in provider networks
US11257002B2 · kind B2 · utility
11Cited by
6References
20Claims
0Family size
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Key dates
| Filing date | Mar 13, 2018 |
| Grant date | Feb 22, 2022 |
| Priority date | — |
| Expiry date | Aug 8, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for dynamic accuracy-based experimentation and deployment of machine learning (ML) models are described. Inference traffic flowing to ML models and the accuracy of the models is analyzed and used to ensure that better performing models are executed more often via model selection. A predictive component can evaluate which model is more likely to be accurate for certain input data elements. Ensemble techniques can combine inference results of multiple ML models to aim to achieve a better overall result than any individual model could on its own.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.