I've read in multiple places that calibration on model results shouldn't be done on the training set (the set that the model is build on), but rather, on a set that the model have not seen. I failed to understand the reasoning.
I tried Googling this but I've seen a lot of conclusions not explanations. Could someone hint me on the reasons behind it?
