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

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

     [ https://issues.apache.org/jira/browse/SPARK-20199?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Nick Pentreath resolved SPARK-20199.
------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.3.0

Issue resolved by pull request 18118
[https://github.com/apache/spark/pull/18118]

> 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
>             Fix For: 2.3.0
>
>
> Spark GradientBoostedTreesModel doesn't have featureSubsetStrategy . It Uses random forest internally ,which have featureSubsetStrategy hardcoded "all". It should be provided by the user to have randomness at the feature level.
> This parameter is available in H2O and XGBoost. 
> Sample from H2O.ai 
> gbmParams._col_sample_rate
> Please provide the parameter . 



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