c-means, hard c-medoids, sequential cluster extraction, kernel function, noise parameter"> c-means, hard c-medoids, sequential cluster extraction, kernel function, noise parameter | Author: Yukihiro Hamasuna and Yasunori Endo" /> JACIII Vol.19 p.759 (2015) | Fuji Technology Press: academic journal publisher
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JACIII Vol.19 No.6 pp. 759-765
doi: 10.20965/jaciii.2015.p0759
(2015)

Paper:

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On a Family of New Sequential Hard Clustering

Yukihiro Hamasuna* and Yasunori Endo**

*Department of Informatics, School of Science and Engineering, Kindai University
3-4-1 Kowakae, Higashi-osaka, Osaka 577-8502, Japan

**Faculty of Engineering, Information and Systems, University of Tsukuba
1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

Received:
April 27, 2015
Accepted:
July 29, 2015
Published:
November 20, 2015
Creative Commons License
Keywords:
hard c-means, hard c-medoids, sequential cluster extraction, kernel function, noise parameter
Abstract
This paper presents a new algorithm of sequential cluster extraction based on hard c-means and hard c-medoids clustering. Sequential cluster extraction means that the algorithm extracts ‘one cluster at a time.’ A characteristic parameter, called a noise parameter, is used in noise clustering based sequential clustering. We propose a novel sequential clustering method called new sequential clustering, extracts an arbitrary number of objects as one cluster by considering the noise parameter as a variable to be optimized. Experimental results with four data sets confirm the effectiveness of our proposal. These results also show that classification results strongly depend on parameter ν and that our proposal is applicable to the first stage in a two-stage clustering algorithm.
Cite this article as:
Y. Hamasuna and Y. Endo, “On a Family of New Sequential Hard Clustering,” J. Adv. Comput. Intell. Intell. Inform., Vol.19 No.6, pp. 759-765, 2015.
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