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Here you see general information about the clustering method.

Clustering Method 'DBSCAN' - General

DBSCAN

DBSCAN regards clusters of objects as dense regions that are separated by regions of low density. A certain minimum number of objects from each cluster is required to be within a certain distance. The number and the distance are user-given. Singletons are considered noise.

  • Publication: Martin Ester, Hans peter Kriegel, Joerg S, and Xiaowei Xu. A density-based algorithm for discovering clusters in large spatial databases with noise. pages 226–231. AAAI Press, 1996.


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Nameprograms/DBSCANClusteringRProgram.jar
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