Abstract
Fuzzy non metric models are a kind of clustering methods, in which the belongingness or the membership grade of each data to each cluster is calculated directly from the dissimilarities between data and the cluster centers are not used. In this paper, we first construct a new fuzzy non metric model by the entropy regularization. Second, we kernelize the proposed method by introducing kernel functions. Third, we consider pairwise constraints with the proposed method. Moreover, we verify the above methods through some numerical examples.
