An Extensional Clustering Algorithm of FCM Based on Intuitionistic Extension Index
Qingfeng Liu · Advanced materials research · 2012
The fuzzy C-means algorithm is an iterative algorithm in which the desired number of clusters C and the initial clustering seeds has to be pre-defined. The seeds are modified in each stage of the algorithm and for each object a degree of membership to each of the clusters is estimated. In this paper, an extensional clustering algorithm of FCM based on an intuitionistic extension index, denoted E-FCM algorithm, is proposed. For comparing the performance of the above mentioned two algorithms, the experimental results of three benchmark data sets show that the E-FCM algorithm outperforms the FCM algorithm.