Thanks for all the suggestions. I have created an issue in Jira. Will work on it soon.
On Sep 14, 2011, at 5:00 AM, Danny Bickson wrote: > 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 <[email protected]> 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 >> <[email protected]> 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 >>
