[jira] [Updated] (FLINK-2157) Create evaluation framework for ML library

["Fabian Hueske (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Fabian Hueske updated FLINK-2157:
---------------------------------
    Fix Version/s:     (was: 0.10.0)
                   1.0.0

> 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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