Method for feature selection in a support vector machine using feature ranking
US7805388B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 30, 2007 |
| Grant date | Sep 28, 2010 |
| Priority date | — |
| Expiry date | Apr 26, 2028 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16B25/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In a pre-processing step prior to training a learning machine, pre-processing includes reducing the quantity of features to be processed using feature selection methods selected from the group consisting of recursive feature elimination (RFE), minimizing the number of non-zero parameters of the system (l0-norm minimization), evaluation of cost function to identify a subset of features that are compatible with constraints imposed by the learning set, unbalanced correlation score, transductive feature selection and single feature using margin-based ranking. The features remaining after feature selection are then used to train a learning machine for purposes of pattern classification, regression, clustering and/or novelty detection.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.