You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@spark.apache.org by "Elisabeth Niederbacher (Jira)" <ji...@apache.org> on 2023/08/17 12:05:00 UTC

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

Elisabeth Niederbacher created SPARK-44848:
----------------------------------------------

             Summary: 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


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. 



--
This message was sent by Atlassian Jira
(v8.20.10#820010)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org