Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
418075 | Computational Statistics & Data Analysis | 2007 | 15 Pages |
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, 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.
Keywords
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Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Marie Chavent, Yves Lechevallier, Olivier Briant,