The lower the better Let’s say test dataset has ratings. These are real ratings provided by users explicitly or implicitly.

  1. We ask our recommender system to generate their own ratings for products.
  2. Then we calculate difference between each rating from test dataset and corresponding rating provided by the system ( where is rating predicted by recommender and is rating provided by user).
  3. To get absolute mean error we calculate mean value of differences calculated on the last step