From a course of AI for Medical Diagnosis, it is explained that validation and test sets should be balanced, 50-50 cases of both cases 0 and 1, so that the performance of the model can be assessed.
But one question arise, test set is suppossed to reflect reality, so it should be imbalanced meanwhile train set should be balanced to help the model to make a distinction between classes, is this approach correct?
