No abstract

No abstract

approach given by Miyamoto and Mukaidono [3]. The regularization approach can also provide the fuzzy c l w tering with crisp regions by introducing the quadratic regularizing function, for example (151). Our approach differs from the regularization approach, and then results are different. In the regularization approach, the meaning of the regularking function is not necwarily Instead of the regularizing function we introduce an explicit classification function which can be interpreted ezcr ilV A n e w h z z Y k-means clustering m&hod is Proposed by introducing crisp regions of clusters. &~u n d a r~~~ Of the redom are determined hYPerbolas admembenhiP are given b y one o r zero in each region. The area between crisp regiom is a fuzzy region, where membership MIues are P r o P o r t i o n d to distances t o crisp regions-A new method is a direct extension of the traditional hard k-means.

Asymmetric proximity, Multidimensional scaling, Two-mode three-way data,