Machine learning system for generating predictions according to varied attributes
US11521744B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 31, 2019 |
| Grant date | Dec 6, 2022 |
| Priority date | — |
| Expiry date | Nov 3, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/044
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes maintaining sets of values for mutable and immutable attributes. Each outcome model of a set of outcome models generates a predicted likelihood of an outcome in response to at least one immutable attribute value and at least one mutable attribute value. A prediction request specifies a first outcome, values for at least one immutable attribute, and values for at least one mutable attribute. The method includes, in response, selecting a group of the sets, where each has values for the immutable attributes that match those of the prediction request. The method includes determining a conditional covariance matrix for the group of sets and then generating a deviation model. The method includes sampling the deviation model to generate sets of mutable attribute values. The method includes, for each of the sets of mutable attribute values, generating, using a selected outcome model, a likelihood of the first outcome occurring.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.