Support vector machine networks for multi-class classification

Document Type

Article

Publication Date

9-1-2005

Abstract

The support vector machine (SVM) has recently attracted growing interest in pattern classification due to its competitive performance. It was originally designed for two-class classification, and many researchers have been working on extensions to multiclass. In this paper, we present a new framework that adapts the SVM with neural networks and analyze the source of misclassification in guiding our preprocessing for optimization in multiclass classification. We perform experiments on the ORL database and the results show that our framework can achieve high recognition rates. © World Scientific Publishing Company.

Identifier

25444471537 (Scopus)

Publication Title

International Journal of Pattern Recognition and Artificial Intelligence

External Full Text Location

https://doi.org/10.1142/S0218001405004320

ISSN

02180014

First Page

775

Last Page

786

Issue

6

Volume

19

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