I am using Surprise to evaluate various recommender system algorithms. I would like to calculate predictions and prediction coverage on all possible user and item permutations. My data is loaded in from predefined splits. My strategy to calculate prediction coverage is to build a full trainset and fit get lists of all users and items iterate through the list and