BIRCH is designed to cluster a large amount of digital records by integrating hierarchical clustering and other clustering methods, including iterative partitioning.
BIRCH offers two concepts, the clustering feature tree and the CF tree clustering feature tree, which are used to summarize the description of the cluster.
These structures facilitate the clustering method to achieve the best speed and scalability in huge databases and also make it effective for incremental and dynamic clustering of incoming objects.
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