Fuzzy C-Means Clustering Algorithm Based on Incomplete Data
In order to solve the problem that the traditional fuzzy c-means(FCM) clustering algorithm can not directly act on incomplete data, a modified algorithm IDFCM(Incomplete Data FCM) based on the FCM algorithm is proposed. The IDFCM algorithm takes the percentage of incomplete data in datasets and its effect on clustering analysis into consideration. Finally, the experimental clustering results of IRIS data and mobile distributed inspected data of the ocean are given, which can clearly prove that the IDFCM algorithm is very efficient for clustering incomplete data.
IDFCM algorithm FCM algorithm fuzzy clustering incomplete datum.
Zhiping Jia Zhiqiang Yu Chenghui Zhang
Department of Computer Science and Technology University of Shandong Jinan, Shandong Province, China Department of Control Science and Engineering University of Shandong Jinan, Shandong Province, China
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
600-604
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）