Self learning adaptive modeling system
US9576262B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 5, 2012 |
| Grant date | Feb 21, 2017 |
| Priority date | — |
| Expiry date | Jul 12, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Self-learning and adaptive modeling is employed with respect to predictive analytics. A hierarchical model structure can be employed comprising a set of predictive models automatically built from accumulated data and distributed across multiple levels. For a given input type, a set of candidate models can be identified across varying levels of granularity, and a best model selected based on a comparison of performance metrics of the models. The best model can then be activated for use in making predictions. Of course, the best model can change based on most recent training performance results, since as more data becomes available more specific models can be developed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.