Linear Clustering of Non-Euclidean Relational Data

Abstract

A linear fuzzy clustering method, which is an extended version of Fuzzy c-Medoids, was proposed in order to extract intrinsic local linear dependencies from relational data. In this research, the characteristic feature of the method with non-Euclidean relational data is discussed through application of data transformation used in non-Euclidean-type Fuzzy (NERF) c-Means. An experimental result demonstrates that the data transformation makes is possible to find a suitable set of medoids, even when the relational measure is not Euclidean.