Parameter learning method, parameter learning apparatus, pattern classification method, and pattern classification apparatus
US7958070B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 27, 2007 |
| Grant date | Jun 7, 2011 |
| Priority date | — |
| Expiry date | May 13, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/172
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A plurality of pieces of learning data, each associated with a class to which the piece of the learning data belong, are input. In each piece of the learning data, a statistical amount of attribute values of elements in each of specific k parts, k being equal to or larger than 1, is calculated. Each piece of the learning data is mapped in a k-dimensional feature space as a vector having the calculated k statistics amounts as elements. Based on each piece of the mapped learning data and the classes to which the pieces of learning data belong, parameters for classifying input data into one of the plurality of classes are learned in the k-dimensional feature space. By using the parameters, pattern classification can be performed with high speed and high accuracy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.