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An SVM classifier incorporating simultaneous noise reduction and feature selection: Illustrative case examples
R. Kumar, , B.D. Kulkarni
Published in
Volume: 38
Issue: 1
Pages: 41 - 49
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. © 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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