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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Consensus Clustering Using Spectral Theory
verfasst von : Mariá Cristina Vasconcelos Nascimento, Franklina Maria Bragion de Toledo, André C. Ponce Leon Ferreira Carvalho
Erschienen in: Advances in Neuro-Information Processing
Verlag: Springer Berlin Heidelberg
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Consensus clustering is a well studied methodology to find partitions through the combination of different formulations or clustering partitions. Different approaches for dealing with this issue using graph clustering have been proposed. Additionally, strategies to find consensus partitions by using graph-based ensemble algorithms have attracted a good deal of attention lately. A particular class of graph clustering algorithms based on spectral theory, named spectral clustering algorithms, has been successfully used in several clustering applications. However, in spite of this, few ensemble approaches based on spectral theory has been investigated. This paper proposes a consensus clustering algorithm based on spectral clustering. Preliminary results presented in this paper show the good potential of the proposed approach.