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Figure 12 | BMC Bioinformatics

Figure 12

From: Learning gene regulatory networks from only positive and unlabeled data

Figure 12

Comparison with unsupervised methods, ARACNE and CLR in simulated data. Average AUROC at different percentage of known positives. The figure shows the difference between supervised and unsupervised methods performance in terms of AUROC (Area Under the ROC curve) obtained in the context of simulated data. The AUROC of both PosOnly and SVMOnly is the same as the order of data predicted by each method is the same. It can be noticed that, similarly for F-Measure, the performance in term of AUROC of supervised methods increases with the percentage of known positive examples. Instead, the performance of unsupervised information theoretic methods are almost the same explaining the fact that unsupervised methods are able to select very precise top regulations but are unable to uncover (by means of a threshold) the complete set of gene regulations of a network.

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