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https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14618468#comment-14618468
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ASF GitHub Bot commented on FLINK-2157:
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Github user tillrohrmann commented on the pull request:
https://github.com/apache/flink/pull/871#issuecomment-119548250
Really good work @thvasilo. I had some minor comments.
The only thing we have to discuss is whether `score` should be part of the
`Predictor` interface. With the current implementation, this implies that every
`Predictor` has to produce a double prediction value. This does not hold for
every `Predictor`. Why not using the `Scorer` class to calculate score values?
> 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: 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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