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