DIVCLUS-T: a monothetic divisive hierarchical clustering method

Marie Chavent 1, 2 Yves Lechevallier 3 Olivier Briant 4
2 CQFD - Quality control and dynamic reliability
INRIA Futurs, Université Bordeaux Segalen - Bordeaux 2, Université Sciences et Technologies - Bordeaux 1, CNRS - Centre National de la Recherche Scientifique : UMR5251
3 AxIS - Usage-centered design, analysis and improvement of information systems
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Paris-Rocquencourt
4 G-SCOP_OC - OC
G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production
Abstract : DIVCLUS-T is a divisive hierarchical clustering algorithm based on a monothetic bipartitional approach allowing the dendrogram of the hierarchy to be read as a decision tree. It is designed for either numerical or categorical data. Like the Ward agglomerative hierarchical clustering algorithm and the k-means partitioning algorithm, it is based on the minimization of the inertia criterion. However, unlikeWard and k-means, it provides a simple and natural interpretation of the clusters. The price paid by construction in terms of inertia by DIVCLUS-T for this additional interpretation is studied by applying the three algorithms on six databases from the UCI Machine Learning repository.
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Marie Chavent, Yves Lechevallier, Olivier Briant. DIVCLUS-T: a monothetic divisive hierarchical clustering method. Computational Statistics and Data Analysis, Elsevier, 2007, 52 (2), pp.687-701. ⟨10.1016/j.csda.2007.03.013⟩. ⟨hal-00260963⟩

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