Fuzzy topological map algorithms. A comprehensive comparison with Kohonen feature map and fuzzy C-mean algorithms
Y.C. Lam, K.F. Cheung · 2002
The function of clustering algorithm is to obtain an optimal reduced set of vectors which can, in some optimal sense, represent a given set of data vectors. Different criteria are used in different algorithms. In this paper, a class of clustering algorithms known as the Fuzzy Topological Map (FTM) algorithm, which is generalized from Kohonen Feature Map (KFM) algorithm and Fuzzy c-Mean (FCM) algorithm, is presented. In particular, KFM algorithm captures the topological structure of the data set, whereas FCM algorithm considers the reduction of an objective function in some L/sub 2/ sense. The FTM algorithm is formulated to subsume both criteria.