SVM classifier incorporating simultaneous noise reduction and feature selection: illustrative case examples

TitleSVM classifier incorporating simultaneous noise reduction and feature selection: illustrative case examples
Publication TypeJournal Article
Year of Publication2005
AuthorsKumar, R, Jayaraman, VK, Kulkarni, BD
JournalPattern Recognition
Volume38
Issue1
Pagination41-49
Date PublishedJAN
Type of ArticleArticle
ISSN0031-3203
Keywordsclassification, conditional entropy, SVM, symbolization
Abstract

A hybrid technique involving symbolization of data to remove noise and use of conditional entropy minima to extract relevant and non-redundant features is proposed in conjunction with support vector machines to obtain more robust classification algorithm. The technique tested on three data sets shows improvements in classification efficiencies. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

DOI10.1016/j.patcog.2004.06.002
Type of Journal (Indian or Foreign)

Foreign

Impact Factor (IF)3.399
Divison category: 
Chemical Engineering & Process Development