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https://issues.apache.org/jira/browse/SPARK-20199?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16030629#comment-16030629
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pralabhkumar commented on SPARK-20199:
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please review the pull request .
https://github.com/apache/spark/commit/16ccbdfd8862c528c90fdde94c8ec20d6631126e
> 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 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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