What parameters to use when normalising training, validation, and testing data?
I am not exactly sure what you mean by &quot;what parameters should be used when normalizing datasets.&quot;
However, it is important to note:
Normalization is a preprocessing step that you do to some or all of the parameters of your model before constructing the model.
But in answer to your question:
You always normalize the same parameters used in both the train and the test set (otherwise how would you be able to compare the results?).