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https://issues.apache.org/jira/browse/SPARK-14409?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15240252#comment-15240252
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Joseph K. Bradley commented on SPARK-14409:
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Thanks for writing this! I just made a few comments too. Wrapping
RankingMetrics seems fine to me, though later on it would be worth
re-implementing it using DataFrames and testing performance changes. The
initial PR should not add new metrics, but follow-up ones can.
Also, we'll need to follow up this issue with one to think about how to use ALS
with CrossValidator. I'll comment on the linked JIRA for that.
> Investigate adding a RankingEvaluator to ML
> -------------------------------------------
>
> Key: SPARK-14409
> URL: https://issues.apache.org/jira/browse/SPARK-14409
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Nick Pentreath
> Priority: Minor
>
> {{mllib.evaluation}} contains a {{RankingMetrics}} class, while there is no
> {{RankingEvaluator}} in {{ml.evaluation}}. Such an evaluator can be useful
> for recommendation evaluation (and can be useful in other settings
> potentially).
> Should be thought about in conjunction with adding the "recommendAll" methods
> in SPARK-13857, so that top-k ranking metrics can be used in cross-validators.
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