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Improved support vector machine generalization using normalized input space

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posted on 06.12.2017, 00:00 by A B M Shawkat Ali, K Smith
Data pre-processing always plays a key role in learning algorithm performance. In this research we consider data pre-processing by normalization for Support Vector Machines (SVMs). We examine the normalization affect across 112 classification problems with SVM using the rbf kernel. We observe a significant classification improvement due to normalization. Finally we suggest a rule based method to find when normalization is necessary for a specific classification problem. The best normalization method is also automatically selected by SVM itself.

History

Editor

Sattar A; Kang B

Parent Title

AI 2006 : advances in artificial intelligence : 19th Australian Joint Conference on Artificial Intelligence, Hobart, Australia, December 4-8, 2006 : proceedings

Start Page

362

End Page

371

Number of Pages

10

ISBN-13

9783540497875

Publisher

Springer

Place of Publication

Berlin, Germany

Open Access

No

External Author Affiliations

Centre for Intelligent and Networked Systems (CINS); Deakin University;

Era Eligible

Yes

Number of Chapters

163

Usage metrics

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