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Posted to issues@spark.apache.org by "Oumar Nour (Jira)" <ji...@apache.org> on 2023/10/03 11:41:00 UTC

[jira] [Commented] (SPARK-44848) MLlib GBTClassifier has wrong impurity method 'variance' instead of 'gini' or 'entropy'.

    [ https://issues.apache.org/jira/browse/SPARK-44848?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17771433#comment-17771433 ] 

Oumar Nour commented on SPARK-44848:
------------------------------------

Hello,

I have the same issue. I want to know if that issue is solved ?

Thanks

> MLlib GBTClassifier has wrong impurity method 'variance' instead of 'gini' or 'entropy'. 
> -----------------------------------------------------------------------------------------
>
>                 Key: SPARK-44848
>                 URL: https://issues.apache.org/jira/browse/SPARK-44848
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib
>    Affects Versions: 3.4.1
>            Reporter: Elisabeth Niederbacher
>            Priority: Major
>
> Impurity method 'variance' should only be used for regressors, *not* classifiers. For classifiers gini and entropy should be available as it is already the case for the RandomForestClassifier [https://spark.apache.org/docs/3.1.3/api/python/reference/api/pyspark.ml.classification.RandomForestClassifier.html] .
> Because of this bug 'minInfoGain' hyperparameter cannot be tuned to combat overfitting. 



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