When dealing with a binary classification problem, where the decision function threshold is being varied from 0 to 1 at step 0.1:
When calculating the Area Under the Curve (AUC) for a ROC Curve plot (x: FPR, y: TPR) is the result AUC value equal for both classes?
When calculating the Area Under the Curve (AUC) for a PR (Precision-Recall) Curve plot (x: TPR, y: PPV) is the result AUC value equal for both classes?
I am not asking about any specific framework or method of calculation, just whether to expect the same AUC values for each class or not when using ROC AUC or PR AUC?