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Posted to issues@spark.apache.org by "Nick Pentreath (JIRA)" <ji...@apache.org> on 2016/03/14 13:30:33 UTC

[jira] [Created] (SPARK-13857) Feature parity for ALS ML with MLLIB

Nick Pentreath created SPARK-13857:
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             Summary: Feature parity for ALS ML with MLLIB
                 Key: SPARK-13857
                 URL: https://issues.apache.org/jira/browse/SPARK-13857
             Project: Spark
          Issue Type: Improvement
          Components: ML
            Reporter: Nick Pentreath


Currently {{mllib.recommendation.MatrixFactorizationModel}} has methods {{recommendProducts/recommendUsers}} for recommending top K to a given user / item, as well as {{recommendProductsForUsers/recommendUsersForProducts}} to recommend top K across all users/items.

Additionally, SPARK-10802 is for adding the ability to do {{recommendProductsForUsers}} for a subset of users (or vice versa).

Look at exposing or porting (as appropriate) these methods to ALS in ML. 

Investigate if efficiency can be improved at the same time (see SPARK-11968).



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