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Fig. 4 | BMC Evolutionary Biology

Fig. 4

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

Fig. 4

Classification performances of the four tested versions of our k-medoids tree clustering algorithm in terms of ARI with respect to the coalescence rate: a the case of 2 to 5 clusters and b the case of 6 to 10 clusters. The four tested versions of our algorithm were 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 varied from 10 to 1 in this simulation. The presented results are the averages taken over all considered numbers of clusters and all considered numbers of tree leaves

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