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https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14608346#comment-14608346
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ASF GitHub Bot commented on FLINK-2157:
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Github user thvasilo commented on the pull request:
https://github.com/apache/flink/pull/871#issuecomment-117202580
I believe that the current code covers the scope of the linked issue. We
can now start reviewing the relevant changes and continue with code cleanup to
bring this to a merge-able state.
Once cleanup is done a few more evaluation score should be added before
merging.
> Create evaluation framework for ML library
> ------------------------------------------
>
> Key: FLINK-2157
> URL: https://issues.apache.org/jira/browse/FLINK-2157
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Labels: ML
> Fix For: 0.10
>
>
> Currently, FlinkML lacks means to evaluate the performance of trained models.
> It would be great to add some {{Evaluators}} which can calculate some score
> based on the information about true and predicted labels. This could also be
> used for the cross validation to choose the right hyper parameters.
> Possible scores could be F score [1], zero-one-loss score, etc.
> Resources
> [1] [http://en.wikipedia.org/wiki/F1_score]
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