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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2014/09/03 20:33:52 UTC

[jira] [Created] (SPARK-3380) DecisionTree: overflow and precision in aggregation

Joseph K. Bradley created SPARK-3380:
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             Summary: 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


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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