I've heard that we should use train dataset's scale for that of test data so they are in line with each other in terms of scale.
And I know we use
transform() function for the test data preprocessing.
But I am wondering how I can apply the same logic to the real-life data set after we successfully save and load a model since I don't think we can use
transform() function anymore.
From what I understand, there must be a way to "extract" mean and standard deviation from the train data set and to apply it for real-life model when using the model we saved already, but how can we do that?