A clustering algorithm based on variance-similarity

doi:10.4028/www.scientific.net/AMM.333-335.1306

LZUFE-KMS

	A clustering algorithm based on variance-similarity
	Li, Zhen Dong 1; Li, Fei 2
	2013
会议名称	2013 2nd International Conference on Measurement, Instrumentation and Automation, ICMIA 2013
会议录名称	Applied Mechanics and Materials
卷号	333-335
期号	0
页码	1306-1309
会议日期	2013-04-23 - 2013-04-24
会议地点	Guilin, China
出版地	DURNTEN-ZURICH
出版者	Trans Tech Publications Ltd, Kreuzstrasse 10, Zurich-Durnten, CH-8635, Switzerland
摘要	Clustering algorithms, like K-means Algorithm, use distances in attribute space to cluster data. However the computation of distances in attribute space influences the accuracy. So innovatively, Variance-Similarity clustering algorithm defines similarity as a function of the attribute variance, and clusters data by the comparison of similarities. In computer simulation, the comparison of Variance-Similarity Algorithm and K-means Algorithm on UCI data sets presents that Variance-Similarity Algorithm has a better clustering accuracy than K-means Algorithm. © (2013) Trans Tech Publications, Switzerland.
关键词	Computer simulation Data mining Attribute values Clustering accuracy k-Means algorithm Variance-similarity
DOI	10.4028/www.scientific.net/AMM.333-335.1306
收录类别	EI ; CPCI-S ; CPCI
语种	英语
WOS研究方向	Engineering ; Instruments & Instrumentation
WOS类目	Engineering, Mechanical ; Instruments & Instrumentation
WOS记录号	WOS:000329080300251
EI入藏号	20133516681106
原始文献类型	Proceedings Paper
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	会议论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/9766
专题	兰州财经大学
作者单位	1.School of Information Engineering, Lanzhou University of Finance and Economics, China; 2.School of Statistics, Lanzhou University of Finance and Economics, China
推荐引用方式 GB/T 7714	Li, Zhen Dong,Li, Fei. A clustering algorithm based on variance-similarity[C]. DURNTEN-ZURICH:Trans Tech Publications Ltd, Kreuzstrasse 10, Zurich-Durnten, CH-8635, Switzerland,2013:1306-1309.