Various Clustering techniques make different assumptions on the composition of the data, generally outlined by some similarity metric and evaluated, one example is, by internal compactness, or even the similarity in between members of the same cluster, and separation, the difference between clusters. Other methods are based on estimated density https://www.businesses.thehabeshaweb.com/author/gcuisabelle/