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JACIII Vol.22 No.2 pp. 163-171
doi: 10.20965/jaciii.2018.p0163
(2018)

Paper:

Power-Regularized Fuzzy Clustering for Spherical Data

Yuchi Kanzawa

Shibaura Institute of Technology
3-7-5 Toyosu, Koto, Tokyo 135-8548, Japan

Received:
June 30, 2017
Accepted:
November 2, 2017
Published:
March 20, 2018
Keywords:
fuzzy clustering, spherical data, power-regularization
Abstract

In this paper, a power-regularization-based fuzzy clustering method is proposed for spherical data. Power regularization has not been previously applied to fuzzy clustering for spherical data. The proposed method is transformed to the conventional fuzzy clustering method, entropy-regularized fuzzy clustering for spherical data (eFCS), for a specified fuzzification parameter value. Numerical experiments on two artificial datasets reveal the properties of the proposed method. Furthermore, numerical experiments on four real datasets indicate that this method is more accurate than the conventional fuzzy clustering methods: standard fuzzy clustering for spherical data (sFCS) and eFCS.

Cite this article as:
Y. Kanzawa, “Power-Regularized Fuzzy Clustering for Spherical Data,” J. Adv. Comput. Intell. Intell. Inform., Vol.22, No.2, pp. 163-171, 2018.
Data files:
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Last updated on Aug. 17, 2018