PCA & LDA in dimension reduction I have a dataset split into training and testing dataset. Then I preprocess the training data using scaling, PCA and LDA. As I recalled, I have to use the centre and standard deviation I get from training data on the testing data. Is it the same too for PCA and LDA? (i.e use the transformation matrix of PCA and LDA from training data?)

Yes, PCA and LDA does not differ from other ML methods. Test data should not be used while standardizing.
