Question on the input and output for ALS.train() and MatrixFactorizationModel.predict().
My input is list of Ratings(user_id, product_id, rating) and my ratings are one a scale of 1-5 (inclusive). When I compute predictions over the superset of all (user_id, product_id) pairs, the ratings produced are on a different scale. The question is this: do I need to normalize the data coming out of predict() to my own scale or does the input need to be different? Thanks!
