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Improved support vector machine generalization using normalized input space

Ali, Shawkat and Smith-Miles, Kate 2006, Improved support vector machine generalization using normalized input space, Lecture notes in computer science, vol. 4304, pp. 362-371.

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Title Improved support vector machine generalization using normalized input space
Author(s) Ali, Shawkat
Smith-Miles, Kate
Journal name Lecture notes in computer science
Volume number 4304
Start page 362
End page 371
Publisher Springer-Verlag
Place of publication Heidelberg, Germany
Publication date 2006
ISSN 0302-9743
1611-3349
Keyword(s) normalization
classification
support vector machines
Summary 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.
Language eng
Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2006, Springer-Verlag
Persistent URL http://hdl.handle.net/10536/DRO/DU:30009052

Document type: Journal Article
Collection: School of Engineering and Information Technology
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