期刊
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
卷 52, 期 1, 页码 92-109出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijar.2010.04.007
关键词
Clustering; Ensemble clustering; Belief functions; Lattice of partitions; Intervals of partitions
In this paper, belief functions, defined on the lattice of intervals partitions of a set of objects, are investigated as a suitable framework for combining multiple clusterings. We first show how to represent clustering results as masses of evidence allocated to sets of partitions. Then a consensus belief function is obtained using a suitable combination rule. Tools for synthesizing the results are also proposed. The approach is illustrated using synthetic and real data sets. (C) 2010 Elsevier Inc. All rights reserved.
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