In terms of papers about ensemble methods/blending I suggest looking at the BigChaos Netflix paper: http://www.*netflixprize*.com/assets/*GrandPrize2009*_BPC_*BigChaos*.pdf See section 7.
Best, Danny Bickson On Wed, Sep 14, 2011 at 11:41 AM, Sean Owen <sro...@gmail.com> wrote: > 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 >
