Figure 13
From: Learning gene regulatory networks from only positive and unlabeled data
Comparison with unsupervised methods, ARACNE and CLR in experimental data. Average F-Measure at different percentage of known positives. The figure shows the difference between supervised and unsupervised methods obtained in the context of experimental data. The performance of supervised methods increases with the percentage of known positive examples. Instead, the performance of unsupervised methods is independent from the percentage of known positive examples.