Ruikang Xing1,*, Chenghai Li1
CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 767-780, 2019, DOI:10.32604/cmc.2019.04500
Abstract In clustering analysis, the key to deciding clustering quality is to determine the optimal number of clusters. At present, most clustering algorithms need to give the number of clusters in advance for clustering analysis of the samples. How to gain the correct optimal number of clusters has been an important topic of clustering validation study. By studying and analyzing the FCM algorithm in this study, an accurate and efficient algorithm used to confirm the optimal number of clusters is proposed for the defects of traditional FCM algorithm. For time and clustering accuracy problems of FCM More >
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