DIVCLUS-T: A monothetic divisive hierarchical clustering method

• Published in: Computational statistics & data analysis Vol. 52; no. 2; pp. 687 - 701
• Main Authors: Chavent, Marie, Lechevallier, Yves, Briant, Olivier
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15-10-2007; Elsevier
• Series: Computational Statistics & Data Analysis
• Subjects: Computer Science; Decision dendrogram; Divisive clustering; Inertia criterion; Machine Learning; Monothetic cluster; Other Statistics; Statistics; Decision dendrogram; Monothetic cluster; Inertia criterion; Divisive clustering
• ISSN: 0167-9473; 1872-7352
• DOI: 10.1016/j.csda.2007.03.013

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, unlike Ward 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.