I am currently working on a multivariate linear regression.
I’m a bit confused about the normalization (mean=0 and standard deviation=1). If we do normalization on our training set, shouldn’t we also normalize our cross-validation set as well as all the new values of X that the model does not know?
I have the same question for image classification with a CNN. If we do pre-processing on our training images, shouldn’t we do the same pre-processing on a new image that the model does not know?