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Fig. 2 | BMC Evolutionary Biology

Fig. 2

From: A new fast method for inferring multiple consensus trees using k-medoids

Fig. 2

Classification performances of the four versions of our k-medoids tree clustering algorithm in terms of ARI with respect to the number of clusters, ranging from 2 to 10. The four tested versions of our algorithm were those based on: 1) SH with RF (), 2) CH with RF (×), 3) SH with RF squared () and 4) CH with RF squared (). The coalescence rate parameter in the HybridSim program was fixed to 5 in this simulation. The presented results are the averages taken over all considered numbers of tree leaves

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