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Trajectory-Based Support Vector Multicategory Classifier.

Authors :
Wang, Jun
Liao, Xiaofeng
Yi, Zhang
Lee, Daewon
Lee, Jaewook
Source :
Advances in Neural Networks - ISNN 2005 (9783540259121); 2005, p857-862, 6p
Publication Year :
2005

Abstract

Support vector machines are primarily designed for binary-class classification. Multicategory classification problems are typically solved by combining several binary machines. In this paper, we propose a novel classifier with only one machine for even multiclass data sets. The proposed method consists of two phases. The first phase builds a trained kernel radius function via the support vector domain decomposition. The second phase constructs a dynamical system corresponding to the trained kernel radius function to decompose data domain and to assign class label to each decomposed domain. Numerical results show that our method is robust and efficient for multicategory classification. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540259121
Database :
Supplemental Index
Journal :
Advances in Neural Networks - ISNN 2005 (9783540259121)
Publication Type :
Book
Accession number :
32862708
Full Text :
https://doi.org/10.1007/11427391_137