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Algorithms of Hard c-Means Clustering Using Kernel Functions in Support Vector Machines
Sadaaki Miyamoto* and Youichi Nakayama**
*Institute of Engineering Mechanics and Systems, University of Tsukuba, Ibaraki 305-8573, Japan
**Graduate School of Systems and Information Engineering, University of Tsukuba, Ibaraki 305-8573, Japan
Received:August 28, 2002Accepted:November 18, 2002Published:February 20, 2003
Keywords:clustering, hard c-means, support vector machine
Abstract
We discuss hard c-means clustering using a mapping into a high-dimensional space considered within the theory of support vector machines. Two types of iterative algorithms are developed. Effectiveness of the proposed method is shown by numerical examples.
Cite this article as:S. Miyamoto and Y. Nakayama, “Algorithms of Hard c-Means Clustering Using Kernel Functions in Support Vector Machines,” J. Adv. Comput. Intell. Intell. Inform., Vol.7 No.1, pp. 19-24, 2003.Data files:
