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Various Clustering techniques make unique assumptions on the framework in the data, often described by some similarity metric and evaluated, by way of example, by interior compactness, or the similarity involving users of exactly the same cluster, and separation, the difference between clusters. Other solutions are according to approximated density http://leaders-ent.com/bbs/board.php?bo_table=free&wr_id=82898
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