DIVCLUS-T: a monothetic divisive hierarchical clustering method

Marie Chavent (1, 2) , Yves Lechevallier (3) , Olivier Briant (4)

1 IMB - Institut de Mathématiques de Bordeaux
2 CQFD - Quality control and dynamic reliability
3 AxIS - Usage-centered design, analysis and improvement of information systems
4 G-SCOP_OC - Optimisation Combinatoire

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.

Mots clés: Divisive clustering; Monothetic cluster; Decision dendrogram; Inertia criterion

Domaines: Autres [stat.ML]; Apprentissage [cs.LG]

Marie Chavent, Yves Lechevallier, Olivier Briant. DIVCLUS-T: a monothetic divisive hierarchical clustering method. Computational Statistics and Data Analysis, 2007, 52 (2), pp.687-701. ⟨10.1016/j.csda.2007.03.013⟩. ⟨hal-00260963⟩