Empirical comparison of a monothetic divisive clustering method with the Ward and the k-means clustering methods
Langue
en
Communication dans un congrès
Ce document a été publié dans
Data Science and Classification, Data Science and Classification, IFCS 2006, 2006-07, Ljubljana. 2006-09p. 83-90
Springer
Résumé en anglais
DIVCLUS-T is a descendant hierarchical clustering methods based on the same monothetic approach than segmentation but from an unsupervised point of view. The dendrogram of the hierarchy is easy to interpret and can be read ...Lire la suite >
DIVCLUS-T is a descendant hierarchical clustering methods based on the same monothetic approach than segmentation but from an unsupervised point of view. The dendrogram of the hierarchy is easy to interpret and can be read as decision tree. We present DIVCLUS-T on a small numerical and a small categorical example. DIVCLUS-T is then compared with two polythetic clustering methods: the Ward ascendant hierarchical clustering method and the k-means partitional method. The three algoritms are applied and compared on six databases of the UCI Machine Learning repository.< Réduire
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