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Table 2 The experimental results on the second data set.

From: A novel approach to phylogenetic tree construction using stochastic optimization and clustering

Dataset GA AAPTC
  mean S.D. high low mean S.D. high low
S21 9.12 0.06 9.79 9.03 9.67 0.01 9.88 9.63
    (53135) (42257)    (78753) (47030)
S22 9.04 0.11 9.22 8.98 9.81 0.03 9.92 9.73
    (69546) (32419)    (68964) (56229)
S23 8.87 0.17 9.14 8.25 9.87 0.05 9.89 9.83
    (57453) (34565)    (76843) (36457)
S24 8.90 0.21 8.91 8.56 9.90 0.09 9.98 9.84
    (56739) (38897)    (66753) (49332)
  1. Table 2 shows the results on the second set of simulated data. We can also see that GA is more likely to fall into local convergence when the objects increase. But AAPTC can get the optimum from given data sets with large number of objects. And AAPTC proposes a more powerful phylogenetic clustering method so it can obtain high qualified solutions no matter how large the number of the objects extends.