DESPOTA: DEndrogram Slicing through a PemutatiOn Test Approach

Dario Bruzzese () and Domenico Vistocco

Journal of Classification, 2015, vol. 32, issue 2, 285-304

Abstract: Hierarchical clustering represents one of the most widespread analytical approaches to tackle classification problems mainly due to the visual powerfulness of the associated graphical representation, the dendrogram. That said, the requirement of appropriately choosing the number of clusters still represents the main difficulty for the final user. We introduce DESPOTA (DEndrogram Slicing through a PermutatiOn Test Approach), a novel approach exploiting permutation tests in order to automatically detect a partition among those embedded in a dendrogram. Unlike the traditional approach, DESPOTA includes in the search space also partitions not corresponding to horizontal cuts of the dendrogram. Applications on both real and syntethic datasets will show the effectiveness of our proposal. Copyright Classification Society of North America 2015

Keywords: Hierarchical clustering; Cluster detection; Permutation tests (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s00357-015-9179-x

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