Self-intelligent improvement in predictive data models
US11410063B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 29, 2019 |
| Grant date | Aug 9, 2022 |
| Priority date | — |
| Expiry date | Jun 11, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/046
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A model assessor retrieves a plurality of predicted outputs from a plurality of models, each predicted output generated using one of the models based on one or more data inputs and a regression model. The model assessor generates a candidate model, which includes as input 1) the one or more data inputs of a selected model of the plurality of models and 2) a predictive output of one or more other models of the plurality of models or one or more other data inputs. A correlation is computed between an actual output and a predicted output of the candidate model, and the model assessor determines if the correlation score exceeds a threshold criteria. If so, the selected model is replaced with the candidate model. Otherwise, the candidate model is deleted.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.