计算机工程与应用2011，Vol.47Issue(18)：17-18,55,3.DOI:10.3778/j.issn.1002-8331.2011.18.005
不同相似度测量方式的模糊C均值聚类分析
Cluster analysis of fuzzy C-mean algorithm based on different similarity estimation distances
摘要
Abstract
Clustering is a key technology widely used in machine learning,pattern recognition,and data mining. Based on different similarity estimation methods,Fuzzy C-Means(FCM) clustering simulation experiments are implemented on three UCI known data sets,test results are analyzed from both sides of accuracy and running efficiency,and it can give a valuable reference for data clustering.关键词
聚类分析/模糊C均值/相似度Key words
cluster analysis/Fuzzy C-Means(FCM)/similarity分类
信息技术与安全科学引用本文复制引用
李中,苑津莎..不同相似度测量方式的模糊C均值聚类分析[J].计算机工程与应用,2011,47(18):17-18,55,3.基金项目
中央高校基本科研业务费专项资金(the Fundamental Research Funds for the Central Universities No.10QG04). （the Fundamental Research Funds for the Central Universities No.10QG04）
