A SUBSPACE CLUSTERING ALGORITHM

被引：0
|
作者：
Zhang, Qiang [1 ]
机构：
[1] Tianjin Univ Sci & Technol, Tianjin, Peoples R China
来源：
2010 6TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS NETWORKING AND MOBILE COMPUTING (WICOM) | 2010年
关键词：
Subspace; projective clustering; histogram; dimensionality reduction;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper we present a new subspace clustering algorithm TGSCA for large dataset with noise. Experiments show that TGSCA can discover clusters both on entire space and subspace; the computation complexity is proximate linear with object's number, space dimension, and clusters' dimension respectively; it is not sensitive to noise; it can find both disjoint clusters or overlap clusters; it can find clusters of arbitrary shape; it is also able to find any number of clusters in any number of dimensions.
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页数：4
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