An improved C-means clustering algorithm

作者：Pi Dechang^*; Xian Chuhua; Qin Xiaolin

来源：Computer Systems Science and Engineering, 2008, 23(1): 43-49.

• clustering analysis
• C-means clustering algorithm
• gravity
• data mining

C-means algorithm needs the number of clusters and it is also sensitive to the initial partition and the input sequence. In order to overcome these disadvantages, an improved C-means algorithm with two-step is proposed. This algorithm assumes that the instances follow normal distribution. To resolve the sensitivity to the input sequence of the instances, these instances are sorted on their densities before clustering, and the proper instances are selected as the initial clustering centers with a definite process. New algorithm employs the theory of gravity to distribute the instances. Experimental results and comparisons are given to illustrate the performance of the new algorithm over that of C-means.

• 出版日期2008-1
• 单位南京航空航天大学