Clustering is a widely used unsupervised data mining technique. In density-based clustering, a cluster is defined as a connected dense component and grows in the direction set by the density. In this paper we present a software system called DBStrata that implements the density-based clustering architecture together with several extensions able to boost the clustering performances and to efficiently identify outliers.
Titolo: | DBStrata: a system for density-based clustering and outlier detection based on stratification |
Autori interni: | |
Data di pubblicazione: | 2011 |
Handle: | http://hdl.handle.net/20.500.11769/82189 |
ISBN: | 978-1-4503-0795-6 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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