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https://issues.apache.org/jira/browse/SPARK-3723?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17520161#comment-17520161
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Apache Spark commented on SPARK-3723:
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User 'zero323' has created a pull request for this issue:
https://github.com/apache/spark/pull/36130
> DecisionTree, RandomForest: Add more instrumentation
> ----------------------------------------------------
>
> Key: SPARK-3723
> URL: https://issues.apache.org/jira/browse/SPARK-3723
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Joseph K. Bradley
> Priority: Minor
> Labels: bulk-closed
>
> Some simple instrumentation would help advanced users understand performance,
> and to check whether parameters (such as maxMemoryInMB) need to be tuned.
> Most important instrumentation (simple):
> * min, avg, max nodes per group
> * number of groups (passes over data)
> More advanced instrumentation:
> * For each tree (or averaged over trees), training set accuracy after
> training each level. This would be useful for visualizing learning behavior
> (to convince oneself that model selection was being done correctly).
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