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https://issues.apache.org/jira/browse/SPARK-2329?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14063133#comment-14063133
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Xiangrui Meng commented on SPARK-2329:
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PR: https://github.com/apache/spark/pull/1270
> Add multi-label evaluation metrics
> ----------------------------------
>
> Key: SPARK-2329
> URL: https://issues.apache.org/jira/browse/SPARK-2329
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Alexander Ulanov
> Assignee: Alexander Ulanov
> Original Estimate: 72h
> Remaining Estimate: 72h
>
> There is no class in Spark MLlib for measuring the performance of multi-label
> classifiers. Multilabel classification is when the document is labeled with
> several labels (classes).
> This task involves adding the class for multilabel evaluation and unit tests.
> The following measures are to be implemented: Precision, Recall and
> F1-measure (1) based on documents averaged by the number of documents; (2)
> per label; (3) based on labels micro and macro averaged; (4) Hamming loss.
> Reference: Tsoumakas, Grigorios, Ioannis Katakis, and Ioannis Vlahavas.
> "Mining multi-label data." Data mining and knowledge discovery handbook.
> Springer US, 2010. 667-685.
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