Self-Organized Similarity based Kernel Fuzzy Clustering Model and Its Applications
Tomoyuki Kuwata, Mika Sato‐Ilic · Institutional Repositories DataBase (IRDB) · 2009
The purpose of this paper is to improve the performance of the kernel fuzzy clustering model by introducing a self-organized algorithm. A conventional kernel fuzzy clustering model is defined as a model which is an improved additive fuzzy clustering. The purpose of this conventional model is to obtain a clearer result by consideration of the interaction of clusters. This paper proposes a fuzzy clustering model based on the idea of self-organized dissimilarity between two objects.