Skip to main content

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.
Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us