Real time feedback from a machine learning system
US12154037B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 29, 2020 |
| Grant date | Nov 26, 2024 |
| Priority date | — |
| Expiry date | Feb 5, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A technique for providing real time feedback from a machine learning system is provided that includes a method and system for interactively training machine learning models. In particular, by separating processing and analysis using static and dynamic models that are trained differently, the disclosed technique enables interactive training and prediction of machine learning models to increase the speed of generating new predictions based on real time feedback. In some cases, a dynamic model is applied to the output of a static model to generate an analysis, a correction of the analysis is received, and the correction is used to retrain the dynamic model. An updated analysis is generated based on reapplying the dynamic model to the output of the static model without having to retrain the static model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.