An overview and new methods in fuzzy clustering

Abstract

Principal methods in nonhierarchical and hierarchical fuzzy clustering are overviewed. In particular, the method of fuzzy c-means is focused upon and recent algorithms in fuzzy c-means are described. It is shown that the concept of regularization plays an important role in the fuzzy c-means. Classification functions induced from fuzzy clustering are discussed and variations of the standard fuzzy c-means are introduced. The hierarchical classification based on the transitive closure is equivalent to the single link method of agglomerative clustering. The roles of the concept of fuzziness in nonhierarchical and hierarchical methods are thus contrasted.