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https://issues.apache.org/jira/browse/SPARK-20199?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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pralabhkumar updated SPARK-20199:
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Description:
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 .
was:
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 .
> 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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