Figure 4From: Predicting the effect of missense mutations on protein function: analysis with Bayesian networksClassifier performance. Performance of naïve Bayes classifier and structure S MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBamrtHrhAL1wy0L2yHvtyaeHbnfgDOvwBHrxAJfwnaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaWaaeGaeaaakeaaimaacqWFse=uaaa@3845@ with parameters learned from incomplete data. The AUC (area under the ROC curve) is plotted against the number of nodes (n) randomly chosen to have missing data within the test examples.Back to article page