Genralized fuzzy cluster loading model

This paper presents a general class of fuzzy cluster loading models. Fuzzy clustering was devised to obtain a natural clustering result vritli a certain degree of belongingness of objects to clusters. Although the concept is rather intuitively defined, it is well known that fuzzy clustering has the power to reveal the complex structure of real data. Instead of the representativeness of fuzzy clustering, it suffers from being difficult to interpret. Specifically, how to explain the obtained clusters is a problem. In order to solve this problem, the fuzzy cluster loading model has been proposed. This model is closely related with the weighted regression model. The weights can control the local spatial heteroscedastic structure of the data. The local structure is unknown and complicated, so various fuzzy cluster loading models are required to identify the structure. Therefore, we define the general class of the fuzzy cluster loading models so as to accommodate the variety of different structures of the data.