[jira] [Commented] (SPARK-10578) pyspark.ml.classification.RandomForestClassifer does not return `rawPrediction` column

["Liang-Chi Hsieh (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-10578?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14743029#comment-14743029 ] 

Liang-Chi Hsieh commented on SPARK-10578:
-----------------------------------------

Hi Karen,

I think these columns are added to RandomForestClassifier in SPARK-9447 by the PR https://github.com/apache/spark/pull/7903.

> pyspark.ml.classification.RandomForestClassifer does not return `rawPrediction` column
> --------------------------------------------------------------------------------------
>
>                 Key: SPARK-10578
>                 URL: https://issues.apache.org/jira/browse/SPARK-10578
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>    Affects Versions: 1.4.0, 1.4.1
>         Environment: CentOS, PySpark 1.4.1, Scala 2.10 
>            Reporter: Karen Yin-Yee Ng
>   Original Estimate: 24h
>  Remaining Estimate: 24h
>
> To use `pyspark.ml.classification.RandomForestClassifer` with `BinaryClassificationEvaluator`, a column called `rawPrediction` needs to be returned by the `RandomForestClassifer`. 
> The PySpark documentation example of `logisticsRegression`outputs the `rawPrediction` column but not `RandomForestClassifier`.
> Therefore, one is unable to use `RandomForestClassifier` with the evaluator nor put it in a pipeline with cross validation.
> A relevant piece of code showing how to reproduce the bug can be found at:
> https://gist.github.com/karenyyng/cf61ae655b032f754bfb
> A relevant post due to this possible bug can also be found at:
> http://apache-spark-user-list.1001560.n3.nabble.com/Issue-with-running-CrossValidator-with-RandomForestClassifier-on-dataset-td23791.html



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