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	Clustering ensembles based on normalized edges
	Li, Yan ; Yu, Jian ; Hao, Pengwei ; Li, Zhulin
	2007
关键词	CONSENSUS
英文摘要	The co-association (CA) matrix was previously introduced to combine multiple partitions. In this paper, we analyze the CA matrix, and address its difference from the similarity matrix using Euclidean distance. We also explore how to find a proper and better algorithm to obtain the final partition using the CA matrix. To get more robust and reasonable clustering ensemble results, a new hierarchical clustering algorithm is proposed by developing a novel concept of normalized edges to measure the similarity between clusters. The experimental results of the proposed approach are compared with those of some single runs of well-known clustering algorithms and other ensemble methods and the comparison clearly demonstrates the effectiveness of our algorithm.; Computer Science, Artificial Intelligence; EI; CPCI-S(ISTP); 0
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/406450]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Li, Yan,Yu, Jian,Hao, Pengwei,et al. Clustering ensembles based on normalized edges. 2007-01-01.

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