Fig. 3
From: A machine learning approach for predicting methionine oxidation sites
ROC curves. From top to bottom: ROC curves and AUC values computed on the evaluation patterns for the RF, SVM and NN models, respectively. The point in each curve that gives the best balance between sensitivity and specificity rates has been marked and annotated with the corresponding “alternative” threshold and efficacy values. Solid black box: AUC = 1 reference area. Dashed gray line: smoothed ROC curve. Solid gray line: random guess