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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2014/11/17 22:55:34 UTC

[jira] [Created] (SPARK-4460) RandomForest classification uses wrong threshold

Joseph K. Bradley created SPARK-4460:
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             Summary: RandomForest classification uses wrong threshold
                 Key: SPARK-4460
                 URL: https://issues.apache.org/jira/browse/SPARK-4460
             Project: Spark
          Issue Type: Bug
          Components: MLlib
    Affects Versions: 1.2.0
            Reporter: Joseph K. Bradley


RandomForest was modified to use WeightedEnsembleModel, but it needs to use a different threshold for prediction than GradientBoosting does.

Fix: WeightedEnsembleModel.scala:70 should use threshold 0.0 for boosting and 0.5 for forests.



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