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https://issues.apache.org/jira/browse/FLINK-32889?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zhipeng Zhang resolved FLINK-32889.
-----------------------------------
Fix Version/s: ml-2.4.0
Assignee: Fan Hong
Resolution: Fixed
> BinaryClassificationEvaluator gives wrong weighted AUC value
> ------------------------------------------------------------
>
> Key: FLINK-32889
> URL: https://issues.apache.org/jira/browse/FLINK-32889
> Project: Flink
> Issue Type: Bug
> Components: Library / Machine Learning
> Affects Versions: ml-2.3.0
> Reporter: Fan Hong
> Assignee: Fan Hong
> Priority: Major
> Labels: pull-request-available
> Fix For: ml-2.4.0
>
>
> BinaryClassificationEvaluator gives wrong AUC value when a weight column
> provided.
> Here is an case from the unit test. The (score, label, weight) of data are:
> {code:java}
> (0.9, 1.0, 0.8),
> (0.9, 1.0, 0.7),
> (0.9, 1.0, 0.5),
> (0.75, 0.0, 1.2),
> (0.6, 0.0, 1.3),
> (0.9, 1.0, 1.5),
> (0.9, 1.0, 1.4),
> (0.4, 0.0, 0.3),
> (0.3, 0.0, 0.5),
> (0.9, 1.0, 1.9),
> (0.2, 0.0, 1.2),
> (0.1, 1.0, 1.0)
> {code}
> PySpark and scikit-learn gives a AUC score of 0.87179, while Flink ML
> implementation gives 0.891168.
>
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