Weighted mean of a pair of clusterings

被引:9
作者
Franek, Lucas [1 ]
Jiang, Xiaoyi [1 ]
He, Changzheng [2 ]
机构
[1] Univ Munster, Dept Math & Comp Sci, D-48149 Munster, Germany
[2] Sichuan Univ, Sch Business Adm, Chengdu 610064, Peoples R China
关键词
Clustering; Weighted mean; Generalized median; Partition distance; PARTITION-DISTANCE; COMPUTATION; ASSIGNMENT; ALGORITHMS; GRAPHS;
D O I
10.1007/s10044-012-0304-8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we introduce the weighted mean of a pair of clusterings. Given two clusterings C (1) and C (2), the weighted mean of C (1) and C (2) is a clustering C (w) that has distances d(C (1), C (w) ) and d(C (w) , C (2)) to C (1) and C (2), respectively, such that d(C (1), C (w) ) + d(C (w) , C (2)) = d(C (1), C (2)) holds for some clustering distance function d. C (w) is defined such that the sum of the distances d(C (1), C (w) ) and d(C (w) , C (2)) is equal to the distance between C (1) and C (2). An algorithm for its computation will be presented. Experimental results on both synthetic and real data will be shown to illustrate the usefulness of the weighted mean concept. In particular, it gives a tool for the cluster ensemble techniques.
引用
收藏
页码:153 / 166
页数:14
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