New Clustering methods for interval data
Langue
en
Article de revue
Ce document a été publié dans
Computational Statistics. 2006, vol. 21, p. 211-229
Springer Verlag
Résumé en anglais
In this paper we propose two clustering methods for interval data based on the dynamic cluster algorithm. These methods use different homogeneity criteria as well as different kinds of cluster representations (prototypes). ...Lire la suite >
Mots clés en italien
Dynamic clustering
interval data
distances
prototypes