会议专题

Weighted Possibilistic C-Means over Large Data Sets

Clustering over large data set may meet a great challenge since data sometime are magnanimity. In this paper, we explore weighted possibilistic clustering algorithm over large data set. The basic idea of the proposed approach is to modify possibilistic c-means (PCM) algorithm to cluster the weighted data points and centroids in units of one data segment Experimental results on both synthetic and real data sets show that our algorithm can save significant memory usage when comparing with PCM algorithm. Furthermore, the proposed algorithm is of an excellent immunity to noise.

large data set weighted cluster possibilitic c-means

Renxia Wan Xiaoliang Dong

College of Information and Computation Science, North University for Nationalities, Yinchuan, Ningxia 750021 China

国际会议

2010 International Conference on Future Information Technology(2010年未来信息技术国际会议 ICFIT 2010)

长沙

英文

281-284

2010-12-14(万方平台首次上网日期,不代表论文的发表时间)