Data minimization using global model explainability
US12406087B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 11, 2022 |
| Grant date | Sep 2, 2025 |
| Priority date | — |
| Expiry date | Aug 13, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F21/6245
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An embodiment analyzes a predictive model and its input data for the predictive model using an explainability algorithm resulting in a feature importance value of a feature. The embodiment analyzes feature values of the feature using a generalization function resulting in a set of candidate feature values. The embodiment determines an alternative feature based on the set of candidate feature values, wherein the alternative feature is a generalization of the feature. The embodiment compares an accuracy of the predictive model to a threshold performance value and, responsive to the accuracy being above the threshold performance value, maps feature values in the input data that are in the set of candidate feature values to a generalized representative value in the generalized domain.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.