You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 05:37:35 UTC
[jira] [Resolved] (SPARK-3380) DecisionTree: overflow and precision
in aggregation
[ https://issues.apache.org/jira/browse/SPARK-3380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-3380.
---------------------------------
Resolution: Incomplete
> DecisionTree: overflow and precision in aggregation
> ---------------------------------------------------
>
> Key: SPARK-3380
> URL: https://issues.apache.org/jira/browse/SPARK-3380
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.1.0
> Reporter: Joseph K. Bradley
> Priority: Minor
> Labels: bulk-closed
>
> DecisionTree does not check for overflows or loss of precision while aggregating sufficient statistics (binAggregates). It uses Double, which may be a problem for DecisionTree regression since the variance calculation could blow up. At the least, it could check for overflow and renormalize as needed.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org