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Table 3 Averaged AUCs for cross-validation measurements on balanced samples using SVMs

From: Learning a Markov Logic network for supervised gene regulatory network inference

Pairwise SVM

C

Pairwise sum

Sum

 

AUC-ROC

AUC-PR

AUC-ROC

AUC-PR

0.001

70.9 ± 3.5

73.1 ± 3.4

82.5 ± 2.3

84.3 ± 2.1

0.01

70.9 ± 3.5

73.1 ± 3.4

82.5 ± 2.3

84.3 ± 2.1

0.1

70.9 ± 3.5

73.1 ± 3.4

82.5 ± 2.3

84.3 ± 2.1

1

76.4 ± 3.1

78.7 ± 3.0

85.2 ± 2.8

87.3 ± 2.5

10

77.5 ± 3.2

79.4 ± 3.5

84.3 ± 3.4

86.3 ± 3.1

100

77.5 ± 3.2

79.4 ± 3.5

84.3 ± 3.4

86.3 ± 3.1

1000

77.5 ± 3.2

79.4 ± 3.5

84.3 ± 3.4

86.3 ± 3.1

  1. The table reports the averaged AUC values and standard deviations obtained with SVMs for thirty ten folds cross-validation experiments conducted on a regulatory network between the genes in G A . The column “Sum” shows the results when the pairwise kernel is derived from the sum of genomic kernels, while the column “Pairwise sum” shows the results obtained using the sum of pairwise kernels derived from each genomic kernel. The results are reported for different values of the regularization parameter C.
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BMC Bioinformatics

ISSN: 1471-2105

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