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https://issues.apache.org/jira/browse/SPARK-4231?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14200426#comment-14200426
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Debasish Das commented on SPARK-4231:
-------------------------------------

[~srowen] I need a standard metric to report the ALS enhancements proposed in 
this PR: https://github.com/apache/spark/pull/2705 and more work that we are 
doing in this direction...

The metric should be consistent for topic modeling using LSA as well as the PR 
can solve LSA/PLSA...I have not yet gone into measures like perplexity etc from 
LDA PRs as they are even more complicated but MAP, prec@k and ndcg@k are the 
measures people reported LDA results as well..

Does the MAP definition I used in this PR looks correct to you ? Let me look 
into the AUC example...

> Add RankingMetrics to examples.MovieLensALS
> -------------------------------------------
>
>                 Key: SPARK-4231
>                 URL: https://issues.apache.org/jira/browse/SPARK-4231
>             Project: Spark
>          Issue Type: Improvement
>          Components: Examples
>    Affects Versions: 1.2.0
>            Reporter: Debasish Das
>             Fix For: 1.2.0
>
>   Original Estimate: 24h
>  Remaining Estimate: 24h
>
> examples.MovieLensALS computes RMSE for movielens dataset but after addition 
> of RankingMetrics and enhancements to ALS, it is critical to look at not only 
> the RMSE but also measures like prec@k and MAP.
> In this JIRA we added RMSE and MAP computation for examples.MovieLensALS and 
> also added a flag that takes an input whether user/product recommendation is 
> being validated.
>  



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