I discovered today that when you train a model that has been already trained with a different input datasets (which may have a different energy binning) the previous instance of the trained model is not deleted. This gives errors in the later stages of the analysis (e.g. will extract all energy bins, from both instances).
I discovered today that when you train a model that has been already trained with a different input datasets (which may have a different energy binning) the previous instance of the trained model is not deleted. This gives errors in the later stages of the analysis (e.g. will extract all energy bins, from both instances).