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https://issues.apache.org/jira/browse/SPARK-15617?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15311218#comment-15311218
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Sean Owen commented on SPARK-15617:
-----------------------------------
Personally I support that. I think that the only metric that makes sense to
expose in the multiclass case, which isn't predicated on one class, is
accuracy. WDYT [~podongfeng]?
> Clarify that fMeasure in MulticlassMetrics and
> MulticlassClassificationEvaluator is "micro" f1_score
> ----------------------------------------------------------------------------------------------------
>
> Key: SPARK-15617
> URL: https://issues.apache.org/jira/browse/SPARK-15617
> Project: Spark
> Issue Type: Documentation
> Components: Documentation, ML, MLlib
> Reporter: Joseph K. Bradley
> Priority: Minor
>
> See description in sklearn docs:
> [http://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html]
> I believe we are calculating the "micro" average for {{val fMeasure:
> Double}}. We should clarify this in the docs.
> I'm not sure if "micro" is a common term, so we should check other libraries
> too.
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