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Posted to issues@flink.apache.org by "Mikio Braun (JIRA)" <ji...@apache.org> on 2015/06/22 15:25:00 UTC
[jira] [Assigned] (FLINK-2157) Create evaluation framework for ML
library
[ https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Mikio Braun reassigned FLINK-2157:
----------------------------------
Assignee: Mikio Braun
> 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: Mikio Braun
> Labels: ML
>
> 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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