Relational Fuzzyc-Lines Clustering Derived from Kernelization of Fuzzyc-Lines
Yuchi Kanzawa · Journal of Advanced Computational Intelligence and Intelligent Informatics · 2014
In this paper, two linear fuzzy clustering algorithms are proposed for relational data based on kernel fuzzyc-means, in which the prototypes of clusters are given by lines spanned in a feature space defined by the kernel which is derived from a given relational data. The proposed algorithms contrast the conventional method in which the prototypes of clusters are given by lines spanned by two representative objects. Through numerical examples, it is shown that the proposed algorithms can capture local sub-structures in relational data.