Automatic correction of indirect bias in machine learning models
US11068797B2 · kind B2 · utility
110Cited by
13References
20Claims
0Family size
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Key dates
| Filing date | Oct 31, 2018 |
| Grant date | Jul 20, 2021 |
| Priority date | — |
| Expiry date | Jan 11, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for detecting indirect bias in machine learning models are provided. A computer-implemented method includes: receiving, by a computer device, a user request to detect transitive bias in a machine learning model; determining, by the computer device, correlations of attributes of neighboring data not included in a dataset of the machine learning model; ranking, by the computer device, the attributes based on the determined correlations; and returning, by the computer device, a list of the ranked attributes to a user that generated the user request.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.