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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 05:35:26 UTC

[jira] [Updated] (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 updated SPARK-3380:
--------------------------------
    Labels: bulk-closed  (was: )

> 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.



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