ROC curve

“Receiver operating characteristic” curve. A common way to examine the performance of a binary classifier. See also Class imbalance

One way to think about the ROC curve is considering the Decision theory. If a false prediction is times more costly than the correct prediction and if we draw the decision boundary accordingly, what would be the accuracy of the model?

If the ROC curve of a model is above another, the model dominates the other; regardless of , the model is always better than the other.

Cross validated: Why are the ROC curves not smooth?