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https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15223875#comment-15223875
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ASF GitHub Bot commented on FLINK-2157:
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GitHub user thvasilo opened a pull request:
https://github.com/apache/flink/pull/1849
[FLINK-2157] [ml] Create evaluation framework for ML library
Using this PR instead of #871 due to rebase issues.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/thvasilo/flink evaluation-rebase
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/flink/pull/1849.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1849
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commit 8ce81d55cfffb70c8971fae47ea315990a7ea97f
Author: Theodore Vasiloudis <[email protected]>
Date: 2016-04-04T09:36:26Z
[FLINK-2157] [ml] Create evaluation framework for ML library
----
> 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
> Assignee: Theodore Vasiloudis
> Labels: ML
> Fix For: 1.0.0
>
>
> 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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