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Table 2 Averaged AUC values (%) of projection method and GHI kernel using sonar data, live disorder data, breast cancer data and NSCLC data

From: Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence

Data sets

Parameters

Projection method

GHI kernel

Sonar

α=1,β=1

82.87  ± 0.99

82.87  ± 0.99

 

α=1,β=2

81.47  ± 0.99

53.42  ± 4.94

 

α=1,β=3

84.02  ± 1.19

54.10  ± 4.92

 

α=2,β=2

84.29  ± 1.54

84.29  ± 1.54

 

α=2,β=3

84.31  ± 1.56

83.06  ± 2.04

 

α=3,β=3

83.62  ± 1.17

83.62  ± 1.17

Live

α=1,β=1

82.87  ± 0.99

82.87  ± 0.99

 

α=1,β=2

81.47  ± 0.99

53.42  ± 4.94

 

α=1,β=3

84.02  ± 1.19

54.10  ± 4.92

 

α=2,β=2

84.29  ± 1.54

84.29  ± 1.54

 

α=2,β=3

84.31  ± 1.56

83.06  ± 2.04

 

α=3,β=3

83.62  ± 1.17

83.62  ± 1.17

Breast

α=1,β=1

96.73  ± 0.11

96.73  ± 0.11

 

α=1,β=2

97.06  ± 0.01

90.12  ± 4.78

 

α=1,β=3

97.01  ± 0.01

75.61  ± 7.44

 

α=2,β=2

96.71  ± 0.11

96.71  ± 0.11

 

α=2,β=3

96.92  ± 0.01

96.96  ± 0.01

 

α=3,β=3

96.63  ± 0.10

96.63  ± 0.10

NSCLC

α=1,β=1

100  ± 0

100  ± 0

 

α=1,β=2

99.72  ± 0.01

64.07  ± 7.42

 

α=1,β=3

61.46  ± 1.57

51.47  ± 5.53

 

α=2,β=2

100  ± 0

100  ± 0

 

α=2,β=3

99.99  ± 0

73.07  ± 8.17

 

α=3,β=3

100  ± 0

100  ± 0

  1. Bold face represents best performance, and no marks are made if two methods show comparable performance