document: Hierarchical model-based clustering of large datasets through fractionation and refractionation The goal of clustering is to identify distinct groups in a dataset . Compared to non-parametric clustering methods like complete linkage , hierarchical model-based clustering has the advantage of offering a way to estimate the number of groups present in the data . However , its computational cost is quadratic in the number of items to be clustered , and it is therefore not applicable to large problems . We review an idea called Fractionation , originally conceived by Cutting , Karger , Pedersen and Tukey for non-parametric hierarchical clustering of large datasets , and describe an adaptation of Fractionation to model-based clustering . A further extension , called Refractionation , leads to a procedure that can be successful even in the difficult situation where there are large numbers of small groups .
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