M. Jahrer & A. Töscher; JMLR W&CP 18:61–74,
Collaborative Filtering Ensemble
This paper provides the solution of the team “commendo” on the Track1 dataset of
the KDD Cup 2011 Dror et al.. Yahoo Labs provides a snapshot of their music-rating database as
dataset for the competition. We get approximately 260 million ratings from 1 million users on
600k items. Timestamp and taxonomy information are added to the ratings. The goal
of the competition was to predict unknown ratings on a testset with RMSE as error
measure. Our ﬁnal submission is a blend of diﬀerent collaborative ﬁltering algorithms.
The algorithms are trained consecutively and they are blended together with a neural
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