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https://issues.apache.org/jira/browse/SPARK-20199?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16038403#comment-16038403
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Kedarnath Reddy commented on SPARK-20199:
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Please look into this feature , as I needed this for my implementation of GBT
in my organization
> 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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