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ASME Press Select Proceedings

International Conference on Information Technology and Computer Science, 3rd (ITCS 2011)

Editor
V. E. Muhin
V. E. Muhin
National Technical University of Ukraine
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W. B. Hu
W. B. Hu
Wuhan University
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ISBN:
9780791859742
No. of Pages:
656
Publisher:
ASME Press
Publication date:
2011

Support vector clustering originates from the concept of support vector machine. It is a robust and unsupervised method. This paper improves the traditional SVC algorithm and presents a multiple spheres weighted support vector clustering (MWSVC) algorithm. The MW-SVC algorithm is suitable for the normal condition that the clustering results of training samples are several clusters. It is fully automatic adaptively, runs fast and has highly accuracy rate. The results of experiment demonstrate the effectiveness of the proposed MW-SVC algorithm.

Abstract
Keywords
Introduction
Kernel Methods
A Multiple Spheres Weighted SVC Algorithm
Experiments
Conclusions
References
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