Classification generation method using combination of mini-classifiers with regularization and uses thereof
US9477906B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 15, 2014 |
| Grant date | Oct 25, 2016 |
| Priority date | — |
| Expiry date | Mar 12, 2035 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH01J49/26
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for classifier generation includes a step of obtaining data for classification of a multitude of samples, the data for each of the samples consisting of a multitude of physical measurement feature values and a class label. Individual mini-classifiers are generated using sets of features from the samples. The performance of the mini-classifiers is tested, and those that meet a performance threshold are retained. A master classifier is generated by conducting a regularized ensemble training of the retained/filtered set of mini-classifiers to the classification labels for the samples, e.g., by randomly selecting a small fraction of the filtered mini-classifiers (drop out regularization) and conducting logistical training on such selected mini-classifiers. The set of samples are randomly separated into a test set and a training set. The steps of generating the mini-classifiers, filtering and generating a master classifier are repeated for different realizations of the separation of the set of samples into test and training sets, thereby generating a plurality of master classifiers. A final classifier is defined from one or a combination of more than one of the master classifie…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.