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ASF GitHub Bot commented on FLINK-2157:
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Github user gaborhermann commented on the issue:
https://github.com/apache/flink/pull/1849
Hi @skonto, I did not have time lately to finish up #2838, but I could
clean it up next week. Although I believe this PR could be merged separately
from mine. (Evaluating ranking recommendations is a bit more complicated.) As
@thvasilo mentioned, the documentation is missing in his PR, but most of the
work is already in place here. I could easily rebase my PR on top of this, if
you don't modify much in the structure of classes. @thvasilo what do you think?
> 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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