I have a dataset which I have split into a training and a test set.
I have thereafter applied normalization on the training set and saved the mean (U) and standard deviation (SD) estimated based on the training set.
- If I apply an algorithm e.g. linear regression how can I apply the coefficients on the test set? Should i normalize the test set using the same U and SD as above and thereafter apply the coefficients?
- If I also normalize the prediction variable (Y), how can i calculate the "real" prediction (unnormalized). Would it be (Y_norm+U)*SD?