[jira] [Commented] (FLINK-2267) Support multi-class scoring for binary classification scores

["Till Rohrmann (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-2267?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16152415#comment-16152415 ] 

Till Rohrmann commented on FLINK-2267:
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I think [~rohits134] is no longer working on this issue. Theoretically you can take it over [~mlipkovich]. However, be aware that there are only very few people reviewing ML PRs at the moment. I would recommend to work rather on something else (e.g. the CEP library).

> Support multi-class scoring for binary classification scores
> ------------------------------------------------------------
>
>                 Key: FLINK-2267
>                 URL: https://issues.apache.org/jira/browse/FLINK-2267
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Theodore Vasiloudis
>            Priority: Minor
>
> Some scores like accuracy, recall and F-score are designed for binary classification.
> They can be used to evaluate multi-class problems as well by using micro or macro averaging techniques.
> This ticket is about creating such an option,  allowing our binary classification metrics to be used in multi-class problems.
> You can check out [sklearn's user guide|http://scikit-learn.org/stable/modules/model_evaluation.html#multiclass-and-multilabel-classification] for more info.



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