Regroupement basé sur la densité
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density-based method
These methods try to explore the data space at high levels of granularity. Thus, they can be used to reconstruct the entire shape of the data distribution. DBSCAN [1] and STING [2] are two classical examples.
a) The density-based method at any particular point in the data space is defined either in terms of the number of data points in a pre-specified volume of its locality or in terms of a smoother kernel density estimate [3]. This method is naturally defined in a continuous space, therefore, arbitrary data types, e.g. time-series, are not quite as easy to use with density-based methods without specialized transformations.
Contributeurs: Claude Coulombe, Imane Meziani, Patrick Drouin, wiki, Sihem Kouache
