Blending

Blending was introduced by the winners of the one million dollar Netflix prize. Netflix organized a contest with the challenge of finding the best model to recommend movies to their users. Netflix users can rate a movie with a rating of one to five stars. Obviously each user wasn't able to rate each movie, so the user movie matrix is sparse. Netflix published an anonymized training and test set. Later researchers found a way to correlate the Netflix data to IMDB data. For privacy reasons, the Netflix data is no longer available. The competition was won in 2008 by a group of teams combining their models. Blending is a form of stacking. The final estimator in blending, however, trains only on a small portion of the train data.