Normalization before data split in Neural Network

Question

I am trying to run a MLP regressor on my dataset with one hidden layer. I am doing a standardization of my data but I want to be clear as whether it matters if I do the standardization after or before splitting the dataset in Training and Test set. I want to know if there will be any difference in my prediction values if I carry out standardization before data split.

Answer 1

Yes and no. If mean and variance of the training and test set are different, standardization can lead to a different outcome.

That being said, a good training and test set should be similar enough so that the data points are distributed in a similar way, and post-split standardization should give the same results.