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. 2012 May 3;7(5):e35077. doi: 10.1371/journal.pone.0035077

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Böck et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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and . Plots comparing distributions of AUC values for ROC graphs for different a and r settings (x- and y-axis), for the synthetic networks of sizes 11, 100 and 1000, using data sets with 20 and 200 time points, respectively. The plots show that results are relatively insensitive over a large range of parameters. Smaller values of the hyperparameter correspond to a more peaked prior distribution, resulting in “sparser” networks. Correspondingly, the figure shows that smaller values of should be chosen for larger networks. Although the effect of changing seems not as pronounced, larger values of correspond to a narrower prior distribution, and should therefore be used if fewer data are available to avoid overfitting.

Inline graphic — and . Plots comparing distributions of AUC values for ROC graphs for different a and r settings (x- and y-axis), for the synthetic networks of sizes 11, 100 and 1000, using data sets with 20 and 200 time points, respectively. The plots show that results are relatively insensitive over a large range of parameters. Smaller values of the hyperparameter correspond to a more peaked prior distribution, resulting in “sparser” networks. Correspondingly, the figure shows that smaller values of should be chosen for larger networks. Although the effect of changing seems not as pronounced, larger values of correspond to a narrower prior distribution, and should therefore be used if fewer data are available to avoid overfitting.