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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2014/11/18 00:32:34 UTC
[jira] [Closed] (SPARK-4460) RandomForest classification uses wrong
threshold
[ https://issues.apache.org/jira/browse/SPARK-4460?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley closed SPARK-4460.
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Resolution: Invalid
Realized this was invalid. Current implementation is fine, except for corner case at 0.5
> 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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