An O(n) clustering method on ultrametric data
| Autor: | Murat Ahat, Said Fouchal, Ivan Lavallée, Marc Bui |
|---|---|
| Přispěvatelé: | Cognitions Humaine et ARTificielle (CHART), Université Paris 8 Vincennes-Saint-Denis (UP8)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Nanterre (UPN)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Laboratoire d'informatique et des systèmes complexes (LAISC), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), École pratique des hautes études (EPHE)-Université Paris 8 Vincennes-Saint-Denis (UP8)-Université Paris Nanterre (UPN)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Tijus, Charles |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Clustering high-dimensional data
Discrete mathematics Correlation clustering Single-linkage clustering 02 engineering and technology Data stream clustering CURE data clustering algorithm 020204 information systems 0202 electrical engineering electronic engineering information engineering Canopy clustering algorithm 020201 artificial intelligence & image processing Cluster analysis Ultrametric space ComputingMilieux_MISCELLANEOUS Mathematics |
| Zdroj: | In The 3rd IEEE conference on Data Mining and Optimization Jun 2011, Putra jaya, Malaysia |
| Popis: | We propose in this paper a novel clustering algorithm in ultrametric spaces. It has a computational cost of O(n). This method is based on the ultratriangle inequality property. Using the order induced by an ultrametric in a given space, we demonstrate how we explore quickly data proximities in this space. We present an example of our results and show the efficiency and the consistency of our algorithm compared with another. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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