Type-2 Context-Based FCM Clustering and Its Model
Sung-Suk Kim, Keun-Chang Kwak · 2014
In this paper, we propose a Type-2 Context-based Fuzzy C-Means (T2-CFCM) clustering algorithm and its linguistic model. This clustering technique builds information granules in the form of Type-2 fuzzy sets and develops clusters by preserving the homogeneity of the clustered patterns associated with the input and output space. The fundamental idea of conditional fuzzy clustering and Linguistic Model (LM) introduced by Pedrycz. Finally, we present the architecture and reasoning scheme of LM based on T2-CFCM clustering.