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https://issues.apache.org/jira/browse/SPARK-7690?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14631575#comment-14631575
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Apache Spark commented on SPARK-7690:
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User 'harsha2010' has created a pull request for this issue:
https://github.com/apache/spark/pull/7475
> MulticlassClassificationEvaluator for tuning Multiclass Classifiers
> -------------------------------------------------------------------
>
> Key: SPARK-7690
> URL: https://issues.apache.org/jira/browse/SPARK-7690
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Ram Sriharsha
> Assignee: Ram Sriharsha
>
> Provide a MulticlassClassificationEvaluator with weighted F1-score to tune
> multiclass classifiers using Pipeline API.
> MLLib already provides a MulticlassMetrics functionality which can be wrapped
> around a MulticlassClassificationEvaluator to expose weighted F1-score as
> metric.
> The functionality could be similar to
> scikit(http://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html)
> in that we can support micro, macro and weighted versions of the F1-score
> (with weighted being default)
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