k-EVCLUS: Clustering Large Dissimilarity Data in the Belief Function Framework

Abstract

In evidential clustering, the membership of objects to clusters is considered to be uncertain and is represented by mass functions, forming a credal partition. The EVCLUS algorithm constructs a credal partition in such a way that larger dissimilarities between objects correspond to higher degrees of conflict between the associated mass functions. In this… (More)
DOI: 10.1007/978-3-319-45559-4_11

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Cite this paper

@inproceedings{Kanjanatarakul2016kEVCLUSCL, title={k-EVCLUS: Clustering Large Dissimilarity Data in the Belief Function Framework}, author={Orakanya Kanjanatarakul and Songsak Sriboonchitta and Thierry Denoeux}, booktitle={BELIEF}, year={2016} }