Is there a general approach that the ROC curve can be used for to validate a model? My understanding is that we can use it to compare different threshold values to determine the best, or even see how different groups behave like with k-fold validation, but that it requires to always be comparing different threshold values. I'm being told that I should be looking at using ROC curves for validating my model (logistic regression), but they do not mean looking at the threshold value of the classification; I keep getting told that it should somehow be used to validate the model in general outside of this.
The model itself doesn't even use cross-validation because the data set itself is fairly large (over a million entries in total). Am I missing something here?