[jira] [Commented] (SPARK-6025) Helper method for GradientBoostedTrees to compute validation error

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-6025?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14340818#comment-14340818 ] 

Apache Spark commented on SPARK-6025:
-------------------------------------

User 'MechCoder' has created a pull request for this issue:
https://github.com/apache/spark/pull/4819

> Helper method for GradientBoostedTrees to compute validation error
> ------------------------------------------------------------------
>
>                 Key: SPARK-6025
>                 URL: https://issues.apache.org/jira/browse/SPARK-6025
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>    Affects Versions: 1.3.0
>            Reporter: Joseph K. Bradley
>            Priority: Minor
>
> Create a helper method for computing the error at each iteration of boosting.  This should be used post-hoc to compute the error efficiently on a new dataset.
> E.g.:
> {code}
> def evaluateEachIteration(data: RDD[LabeledPoint], evaluator): Array[Double]
> {code}
> Notes:
> * It should run in the same big-O time as predict() by keeping a running total (residual).
> * A different method name could be good.
> * It could take an evaluator and/or could evaluate using the training metric by default.



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