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https://issues.apache.org/jira/browse/SPARK-14409?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15897198#comment-15897198
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Danilo Ascione commented on SPARK-14409:
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Thank you [~mlnick] for taking time to thing about this.
I like the generalization for the most common scenarios.
The Evaluator approach is already implemented in
[#16618|https://github.com/apache/spark/pull/16618]. I'll find time to update
the PR with the proposed generalization and the ranking metrics computations as
UDFs.
> 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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