Dataset classification quantification
US9424530B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 26, 2015 |
| Grant date | Aug 23, 2016 |
| Priority date | — |
| Expiry date | Jan 26, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, computing systems and computer program products implement embodiments of the present invention that include selecting a training dataset including training instances having respective training features, and applying a classifier to the training dataset, thereby generating a training classification that assigns, to each of the training instances, one of a plurality of categories, the classifier having an expected classification. A classification bias is detected in the training classification relative to the expected classification, and in response to the classification bias, a calibration matrix is defined based on the training features, and the classification bias. A production dataset including production instances is selected, and the classifier and the calibration matrix are applied to the production dataset, thereby generating a production classification quantification that assigns, to each of the production instances, one of the plurality of categories.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.