Research and Improvement of Clustering Algorithm in Data Mining

摘要：

this paper is a cluster analysis algorithm research carried out based on the existing data mining,which focuses on the current popular and commonly used K-means algorithm,and presents an improved K-harmonic means clustering algorithm through using a new distance measure. Through the regulation of distance metric parameters can achieve better clustering effects than the traditional K-harmonic means,and has an advantage both in run time and number of iterations.

关键词： data mining:clustering analysis:K-means algorithm

作者: Ren Jingbiao Yin Shaohong

作者单位: Tianjin Polytechnic University

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

会议地点: 成都

会议语种:英文

页码: 4990-4993

在线出版日期: 2010-04-16（万方平台首次上网日期，不代表论文的发表时间）