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From "Debasish Das (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-4675) Find similar products and similar users in MatrixFactorizationModel
Date Thu, 11 Dec 2014 02:34:12 GMT

    [ https://issues.apache.org/jira/browse/SPARK-4675?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14242034#comment-14242034
] 

Debasish Das commented on SPARK-4675:
-------------------------------------

[~josephkb] how do we validate that low dimension space is giving more meaningful similarities
than the feature space (which is sparse) ?

> Find similar products and similar users in MatrixFactorizationModel
> -------------------------------------------------------------------
>
>                 Key: SPARK-4675
>                 URL: https://issues.apache.org/jira/browse/SPARK-4675
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>            Reporter: Steven Bourke
>            Priority: Trivial
>              Labels: mllib, recommender
>
> Using the latent feature space that is learnt in MatrixFactorizationModel, I have added
2 new functions to find similar products and similar users. A user of the API can for example
pass a product ID, and get the closest products. 



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