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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2014/08/01 16:34:38 UTC

[jira] [Updated] (SPARK-2768) Add product, user recommend method to MatrixFactorizationModel

     [ https://issues.apache.org/jira/browse/SPARK-2768?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Xiangrui Meng updated SPARK-2768:
---------------------------------

    Assignee: Sean Owen

> Add product, user recommend method to MatrixFactorizationModel
> --------------------------------------------------------------
>
>                 Key: SPARK-2768
>                 URL: https://issues.apache.org/jira/browse/SPARK-2768
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>    Affects Versions: 1.0.1
>            Reporter: Sean Owen
>            Assignee: Sean Owen
>            Priority: Minor
>             Fix For: 1.1.0
>
>
> Right now, MatrixFactorizationModel can only predict a score for one or more (user,product) tuples. As a comment in the file notes, it would be more useful to expose a recommend method, that computes top N scoring products for a user (or vice versa -- users for a product).



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