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Table 2 Means and standard derivations of AUC values of prediction of subnetwork genes on simulation data sets with different signal-to-noise levels for netSVM, other network-based methods and gene-based methods.

From: Identifying cancer biomarkers by network-constrained support vector machines

SNR
(db)
network-based method gene-based method
  netSVM F-norm SVM Larsnet Chuang's method SVM Lasso T-test
10 0.89 ± 0.00 0.80 ± 0.03 0.64 ± 0.02 0.85 ± 0.03 0.79 ± 0.00 0.62 ± 0.02 0.78 ± 0.03
8 0.90 ± 0.02 0.81 ± 0.03 0.64 ± 0.02 0.81 ± 0.03 0.79 ± 0.02 0.62 ± 0.01 0.78 ± 0.04
6 0.90 ± 0.02 0.81 ± 0.03 0.63 ± 0.02 0.84 ± 0.03 0.79 ± 0.03 0.62 ± 0.02 0.77 ± 0.04
4 0.90 ± 0.02 0.81 ± 0.04 0.63 ± 0.01 0.82 ± 0.02 0.80 ± 0.02 0.61 ± 0.01 0.78 ± 0.04
2 0.90 ± 0.02 0.80 ± 0.03 0.63 ± 0.01 0.83 ± 0.02 0.79 ± 0.02 0.62 ± 0.02 0.77 ± 0.04
0 0.90 ± 0.03 0.81 ± 0.03 0.63 ± 0.02 0.83 ± 0.04 0.79 ± 0.03 0.61 ± 0.02 0.78 ± 0.04
-2 0.91 ± 0.02 0.80 ± 0.03 0.63 ± 0.02 0.82 ± 0.03 0.80 ± 0.02 0.61 ± 0.02 0.79 ± 0.03
-4 0.89 ± 0.02 0.79 ± 0.03 0.63 ± 0.01 0.83 ± 0.02 0.78 ± 0.02 0.61 ± 0.02 0.78 ± 0.03
-6 0.88 ± 0.02 0.79 ± 0.03 0.63 ± 0.02 0.83 ± 0.04 0.75 ± 0.02 0.61 ± 0.01 0.76 ± 0.05
-8 0.89 ± 0.02 0.77 ± 0.03 0.63 ± 0.01 0.83 ± 0.03 0.75 ± 0.04 0.61 ± 0.01 0.77 ± 0.04
-10 0.87 ± 0.03 0.75 ± 0.03 0.63 ± 0.02 0.80 ± 0.04 0.74 ± 0.03 0.61 ± 0.01 0.76 ± 0.04
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