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Posted to issues@spark.apache.org by "Danilo Ascione (JIRA)" <ji...@apache.org> on 2017/03/04 10:14:45 UTC
[jira] [Commented] (SPARK-14409) Investigate adding a
RankingEvaluator to ML
[ https://issues.apache.org/jira/browse/SPARK-14409?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15895619#comment-15895619 ]
Danilo Ascione commented on SPARK-14409:
----------------------------------------
I can help with both PR. Please consider that the solution in [PR 16618|https://github.com/apache/spark/pull/16618] is a Dataframe api based version of that in [PR 12461|https://github.com/apache/spark/pull/12461]. Any way, I'd like to help review an alternative solution. Thanks!
> 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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