Binary signal classifiers that tolerate incorrect training data
US10719783B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | May 16, 2019 |
| Grant date | Jul 21, 2020 |
| Priority date | — |
| Expiry date | May 16, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/1822
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
There are disclosed devices, system and methods for a machine learning binary classifier automatically tolerating training data that is incorrect by determining a correct and an incorrect likelihood ratio that each training data entry has a correctly and an incorrectly labeled output. The correct and an incorrect likelihood ratio are combined with a correct and an incorrect priori odds ratio that the set of training data entries have correctly and incorrect labeled output labels. These two combinations are a correct probability and an incorrect probability that each entry of the set of entries has a correctly and an incorrect labeled output. A logistic regression model if fit to a combination of the correct probability and the incorrect probability for each training data entry to complete the training.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.