Distinctive Clustering techniques make unique assumptions to the structure of the data, often outlined by some similarity metric and evaluated, one example is, by internal compactness, or perhaps the similarity among members of a similar cluster, and separation, the distinction between clusters. Other strategies are based on approximated density and http://emjun.com/index.php?mid=mmm&document_srl=1251918