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From "Sachin Goel (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-2267) Support multi-class scoring for binary classification scores
Date Fri, 17 Jul 2015 19:38:09 GMT

    [ https://issues.apache.org/jira/browse/FLINK-2267?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14631792#comment-14631792

Sachin Goel commented on FLINK-2267:

Hi [~rohits134], you'd get a DataSet[(Double,Double)] and are expected to calculate the Micro
and macro averages. You can read about them either on the sk-learn link mentioned, or just
google it.

Take a look at the currently ongoing work here: https://github.com/apache/flink/pull/891.
You should perhaps build on that work.

Ask someone else to assign it to you [try the IRC]. I seem to be unable to do that too. :')

> 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
> 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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