[jira] [Commented] (SPARK-3723) DecisionTree, RandomForest: Add more instrumentation
[ https://issues.apache.org/jira/browse/SPARK-3723?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17520162#comment-17520162 ] Apache Spark commented on SPARK-3723: - 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). -- This message was sent by Atlassian Jira (v8.20.1#820001) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-3723) DecisionTree, RandomForest: Add more instrumentation
[ https://issues.apache.org/jira/browse/SPARK-3723?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17520161#comment-17520161 ] Apache Spark commented on SPARK-3723: - 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). -- This message was sent by Atlassian Jira (v8.20.1#820001) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-3723) DecisionTree, RandomForest: Add more instrumentation
[ https://issues.apache.org/jira/browse/SPARK-3723?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15347489#comment-15347489 ] Apache Spark commented on SPARK-3723: - User 'smurching' has created a pull request for this issue: https://github.com/apache/spark/pull/13881 > DecisionTree, RandomForest: Add more instrumentation > > > Key: SPARK-3723 > URL: https://issues.apache.org/jira/browse/SPARK-3723 > Project: Spark > Issue Type: Improvement > Components: MLlib >Reporter: Joseph K. Bradley >Priority: Minor > > 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). -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
