This isn&#x27;t something I know about, but I would think that for a classification problem, if the right loss function is used then the NN should learn to maximise the chance that the true answer is within the intervals it provides. However...<p>&gt; If we test the net and find such a confidence associated with an incorrect classification more frequently than predicted then we can say that the confidence is objectively incorrect.<p>On the test data performance is never going to match the NN&#x27;s training set performance, so it would always overestimate its confidence.