[jira] [Commented] (SPARK-3159) Check for reducible DecisionTree

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-3159?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16368106#comment-16368106 ] 

Apache Spark commented on SPARK-3159:
-------------------------------------

User 'asolimando' has created a pull request for this issue:
https://github.com/apache/spark/pull/20632

> Check for reducible DecisionTree
> --------------------------------
>
>                 Key: SPARK-3159
>                 URL: https://issues.apache.org/jira/browse/SPARK-3159
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>            Reporter: Joseph K. Bradley
>            Priority: Minor
>
> Improvement: test-time computation
> Currently, pairs of leaf nodes with the same parent can both output the same prediction.  This happens since the splitting criterion (e.g., Gini) is not the same as prediction accuracy/MSE; the splitting criterion can sometimes be improved even when both children would still output the same prediction (e.g., based on the majority label for classification).
> We could check the tree and reduce it if possible after training.
> Note: This happens with scikit-learn as well.



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