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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
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