JACIII Vol.19 No.5 pp. 632-638
doi: 10.20965/jaciii.2015.p0632


On Objective-Based Rough Clustering with Fuzzy-Set Representation

Naohiko Kinoshita*, Yasunori Endo**, and Ken Onishi***

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

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

***Toyota Motor Corporation
1 Toyota-Cho, Toyota, Aichi 471-8571, Japan

January 31, 2015
June 16, 2015
September 20, 2015
clustering, rough clustering, optimization, fuzzy set
The rough clustering algorithm we proposed based on the optimization of objective function (RCM) has a problem because conventional rough clustering algorithm results do not ensure that solutions are optimal. To solve this problem, we propose rough clustering algorithms based on optimization of an objective function with fuzzy-set representation. This yields more flexible results than RCM. We verify algorithm effectiveness through numerical examples.
Cite this article as:
N. Kinoshita, Y. Endo, and K. Onishi, “On Objective-Based Rough Clustering with Fuzzy-Set Representation,” J. Adv. Comput. Intell. Intell. Inform., Vol.19 No.5, pp. 632-638, 2015.
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