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Simultaneous Application of Fuzzy Clustering and Quantification with Incomplete Categorical Data
Katsuhiro Honda, Yoshihito Nakamura, and Hidetomo Ichihashi
Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka, Japan
Received:September 25, 2003Accepted:March 29, 2004Published:July 20, 2004
Keywords:fuzzy clustering, homogeneity analysis, missing value
Abstract
This paper proposes the simultaneous application of homogeneity analysis and fuzzy clustering with incomplete data. Taking into account the similarity between the loss function for homogeneity analysis and the least squares criterion for principal component analysis, we define the new objective function in a formulation similar to linear fuzzy clustering with missing values. Numerical experiments demonstrate the feasibility of the proposed method.
Cite this article as:K. Honda, Y. Nakamura, and H. Ichihashi, “Simultaneous Application of Fuzzy Clustering and Quantification with Incomplete Categorical Data,” J. Adv. Comput. Intell. Intell. Inform., Vol.8 No.4, pp. 397-402, 2004.Data files:
