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https://issues.apache.org/jira/browse/SPARK-2768?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-2768.
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Resolution: Fixed
Fix Version/s: 1.1.0
Issue resolved by pull request 1687
[https://github.com/apache/spark/pull/1687]
> 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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