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SVMV - A Novel Algorithm for the Visualization of SVM Classification Results.

Authors :
Wang, Jun
Yi, Zhang
Zurada, Jacek M.
Lu, Bao-Liang
Yin, Hujun
Wang, Xiaohong
Wu, Sitao
Wang, Xiaoru
Li, Qunzhan
Source :
Advances in Neural Networks - ISNN 2006; 2006, p968-973, 6p
Publication Year :
2006

Abstract

In this paper, a novel algorithm, called support vector machine visualization (SVMV), is proposed. The SVMV algorithm is based on support vector machine (SVM) and self-organizing mapping (SOM). High dimensional data and binary classification results can be visualized in a low dimensional space. Compared with other traditional visualization algorithms like SOM and Sammon's mapping algorithm, the SVMV algorithm can deliver better visualization on classification results. Experimental results corroborate the effectiveness and usefulness of SVMV. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540344391
Database :
Supplemental Index
Journal :
Advances in Neural Networks - ISNN 2006
Publication Type :
Book
Accession number :
32883757
Full Text :
https://doi.org/10.1007/11759966_142