8 min readRecommender Systems
The Model That Picks Its Own Training Data
Two fitted offsets deliver 66% of a recommender’s gain in accuracy before any latent factor is learned, the error is 1.28 times worse for the users who have said least, only 30% of the catalogue reaches anyone’s top ten with no explicit popularity term in the model, and after six rounds of self-selected data the system is 1.14 times worse exactly where it stopped looking.
Machine LearningStatistics