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On data based learning using support vector clustering

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1 Author(s)
Ribeiro, B. ; Dept. of Informatics Eng., Coimbra Univ., Portugal

This paper addresses the effect of applying clustering algorithms, based on a distance metric rule, prior to support kernel learning in classification and regression problems. Self-Organising Maps (SOMs), which place emphasis in data domain description, and K-means clustering algorithms have been selected before applying a support vector algorithm which is based on a margin rule. Moreover, the recently developed support vector clustering algorithm, based on a cluster boundary rule, is applied in benchmark problems for comparison.

Published in:

Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on  (Volume:5 )

Date of Conference:

18-22 Nov. 2002

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