Bounding error rate of a classifier based on worst likely assignment
US7899766B2 · kind B2 · utility
Inventors
Key dates
| Filing date | Feb 7, 2008 |
| Grant date | Mar 1, 2011 |
| Priority date | — |
| Expiry date | Aug 28, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Given a set of training examples—with known inputs and outputs—and a set of working examples—with known inputs but unknown outputs—train a classifier on the training examples. For each possible assignment of outputs to the working examples, determine whether assigning the outputs to the working examples results in a training and working set that are likely to have resulted from the same distribution. If so, then add the assignment to a likely set of assignments. For each assignment in the likely set, compute the error of the trained classifier on the assignment. Use the maximum of these errors as a probably approximately correct error bound for the classifier.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.