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The time needed to apply a hierarchical clustering algorithm is most often dominated by the number of computations of a pairwise dissimilarity measure. Such a constraint, for larger data sets, puts at a disadvantage the use of all the classical linkage criteria but the single linkage one. However, it is known that the single linkage clustering algo...
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Context 1
... Please note that, by definition, the weighted edges appear in an MST in no particular order -for instance, the Prim [51] algorithm's output depends on the permutation of inputs. Therefore, having established the above relation between the Genie clustering and an MST, in Figure 5 we provide a pseudocode of the algorithm that guarantees the right cluster merge order. The procedure resembles the Kruskal [37] algorithm and is fully concordant with our method's description in Section 3.1. ...
Context 2
... dissimilarity measure is selected via the metric argument, e.g., "euclidean", "manhattan", "maximum", "hamming", "levenshtein", "dinu", etc. The thresholdGini argument can be used to define the threshold for the Gini-index (denoted with g in Figure 5). Finally, the useVpTree argument can be used to switch between the MST algorithms given in Figures 6 (the default) and 7. ...
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