normalising data before data split or after?
I have a question, I wanted to separate my data into train and test set, should I now apply normalisation before or after the split?
someone told me it would make more sense to do normalisation after the split for each train /test data... but why? if I do so, I would normalise on the specific ranges of values regarding the train / test dataset... but if I use split before, I will normalise on the whole range, isn't that more general, and therefore more representative regarding my dataset? or does it make no difference at all?