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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2014/09/30 21:43:33 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 ]
Joseph K. Bradley updated SPARK-3380:
-------------------------------------
Priority: Minor (was: Major)
> 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
>
> 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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