Improved support vector machine generalization using normalized input space
Data(s) |
01/01/2006
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Resumo |
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. <br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
Springer-Verlag |
Relação |
http://dro.deakin.edu.au/eserv/DU:30009052/n20061171.pdf http://dx.doi.org/10.1007/11941439_40 |
Direitos |
2006, Springer-Verlag |
Palavras-Chave | #normalization #classification #support vector machines |
Tipo |
Journal Article |