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https://issues.apache.org/jira/browse/SPARK-20199?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15984161#comment-15984161
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Yan Facai (颜发才) commented on SPARK-20199:
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The work is easy, however Public method is added and some adjustments are
needed in inner implementation. Hence, I suggest to delay it until one expert
agree to shepherd the issue.
I have two questions:
1. For both GBDT and RandomForest share the attribute, we can pull
`featureSubsetStrategy` parameter up to either TreeEnsembleParams or
DecisionTreeParams. Which one is appropriate?
2. Is it right to add new parameter `featureSubsetStrategy` to Strategy class?
Or add it to DecisionTree's train method?
> GradientBoostedTreesModel doesn't have Column Sampling Rate Paramenter
> -----------------------------------------------------------------------
>
> 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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