Simultaneous Application of Fuzzy Clustering and Quantification with Incomplete Categorical Data
Katsuhiro Honda, Yoshihito Nakamura, Hidetomo Ichihashi · Journal of Advanced Computational Intelligence and Intelligent Informatics · 2004
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.