User 2070 | 7/1/2015, 4:02:53 PM
How can I create a recommendation where the set of items recommended is within certain side itemdata categories? I've reviewed the online documentation for gl.create and there is much info about how to include side itemdata and userdata, but none that addresses this. Example:
- create model with side itemdata
data = standard (user_id, item_id, rating tupple) sframe
side item_data = (item_type_a, item_type_b, item_type_c, etc) (e.g. all item_ids map to 1 categorical type)
m3 = gl.ranking_factorization_recommender.create(data,target='rating',item_id='item_id',item_data=item_type)
Recommendation for new user (with no category constraints) is simple:
This returns list of recommended itemids, spanning all itemtype categories
But: how can I create a "constrained recommendation" limited to a specific set of item_type categories?
- m3.recommend(['new_user'))['item_id'] but limit the recommendations to items in, say, only (item_type_b or item_type_c)?
The example in the user guide, 7.6, questions 12-14 is similar in spirit, but not applicable as there the recommender model is predicting category tags, where here the "tag" is side data. Any suggestions on how to proceed?