There isn't. For the recommenders that work by computing an estimated preference value for items, I suppose you could average their estimates and rank by that.
More crudely, you could stitch together the recommendations of recommender 1 and 2 by taking the top 10 amongst each of their top recommendations -- averaging estimates where an item appears in both lists. That's much less work for you; it's not quite as "accurate". On Wed, Sep 14, 2011 at 2:39 AM, Daniel Xiaodan Zhou <danith...@gmail.com> wrote: > Is there an EnsembleRecommender or CompoundRecommender that takes input from > other recommender algorithms and combine them to generate better results? If > not, I'm thinking to contribute a patch. Any suggestions on implementation? > Thanks. > > Daniel Zhou
