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Joseph K. Bradley commented on SPARK-14409: ------------------------------------------- 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org