[jira] [Commented] (SPARK-20199) GradientBoostedTreesModel doesn't have featureSubsetStrategy parameter

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

    [ https://issues.apache.org/jira/browse/SPARK-20199?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16025932#comment-16025932 ] 

pralabhkumar commented on SPARK-20199:
--------------------------------------

1) Have Created pull request.

Basically Moved 

1) featureSubsetStrategy to TreeEnsembleParams instead of having it on RandomForestParams . So that it can be used for both Random Forest and GBT
2 ) Changed DecisionTreeRegressor private train method to pass featureSubsetStrategy
3) To Test changed GradientBoostedTreeClassifierExample with
val gbt = new GBTClassifier()
      .setLabelCol("indexedLabel")
      .setFeaturesCol("indexedFeatures")
      .setMaxIter(10)
      .setFeatureSubsetStrategy("auto") 



> GradientBoostedTreesModel doesn't have  featureSubsetStrategy parameter
> -----------------------------------------------------------------------
>
>                 Key: SPARK-20199
>                 URL: https://issues.apache.org/jira/browse/SPARK-20199
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, MLlib
>    Affects Versions: 2.1.0
>            Reporter: pralabhkumar
>
> Spark GradientBoostedTreesModel doesn't have Column  sampling rate parameter . This parameter is available in H2O and XGBoost. 
> Sample from H2O.ai 
> gbmParams._col_sample_rate
> Please provide the parameter . 



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