[
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 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
