FCM clustering algorithm based on information entropy
Fengling Wang · Jisuanji gongcheng yu sheji · 2010
For the fuzzy clustering existed the problem of data uniformity contraction,a new method of fuzzy clustering algorithm is proposed, and the simulation experiment is conducted.Fuzzy C-means(FCM) algorithm is the objective function through iterative optimization to receive the dataset partition.With the information entropy as the fuzzy C-means algorithmconstraints,the derivation process of the new algorithm is given,the clustering center and membership of the new fuzzy C-means clustering algorithm are obtained.The results show that the modified algorithm gets the better validity and performance than the fuzzy C-means algorithm,and received the better results in the application.