Processing dynamic data within an adaptive oracle-trained learning system using curated training data for incremental re-training of a predictive model
US10614373B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 19, 2014 |
| Grant date | Apr 7, 2020 |
| Priority date | — |
| Expiry date | Jul 21, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In general, embodiments of the present invention provide systems, methods and computer readable media for an adaptive oracle-trained learning framework for automatically building and maintaining models that are developed using machine learning algorithms. In embodiments, the framework leverages at least one oracle (e.g., a crowd) for automatic generation of high-quality training data to use in deriving a model. Once a model is trained, the framework monitors the performance of the model and, in embodiments, leverages active learning and the oracle to generate feedback about the changing data for modifying training data sets while maintaining data quality to enable incremental adaptation of the model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.