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Posted to issues@spark.apache.org by "zhengruifeng (JIRA)" <ji...@apache.org> on 2019/06/03 09:45:00 UTC

[jira] [Created] (SPARK-27925) Better control numBins of curves in BinaryClassificationMetrics

zhengruifeng created SPARK-27925:
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             Summary: Better control numBins of curves in BinaryClassificationMetrics
                 Key: SPARK-27925
                 URL: https://issues.apache.org/jira/browse/SPARK-27925
             Project: Spark
          Issue Type: Improvement
          Components: ML
    Affects Versions: 3.0.0
            Reporter: zhengruifeng


In case of large datasets with tens of thousands of partitions, current curve down-sampling method tend to generate much more bins than the value set by #numBins.

Since in current impl, grouping is done within partitions, that is to say, each partition contains at least one bin.

A more reasonable way is to bring the grouping op forward into the sort op, then we can directly set the #bins as the #partitions, and regard one partition as one bin.

 



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