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

["Nick Pentreath (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-13857?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Nick Pentreath reassigned SPARK-13857:
--------------------------------------

    Assignee: Nick Pentreath

> 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
>            Assignee: 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).



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org