Receiver operating characteristic (ROC) analysis is a method for evaluating successful discrimination. The machine learning model (SVM) predicts chemicals that were not in the training data. Predictions for these new chemicals are then compared to the ground truth. Success is defined by high positive (sensitivity) and low false-positive (1 − specificity) rates. Subsequently, an ROC plot shows the relationship between these two rates. The best possible performance is an area under the curve (AUC) of 1.0.