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https://issues.apache.org/jira/browse/SPARK-19282?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-19282:
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Description:
Currently it isn't clear hot to get the max depth of a
RandomForestRegressionModel (eg, after doing a grid search)
It is possible to call
{{regressor._java_obj.getMaxDepth()}}
but most other decision trees allow
{{regressor.getMaxDepth()}}
UPDATE: This is just for Spark R. SEe [SPARK-20498] for Python.
was:
Currently it isn't clear hot to get the max depth of a
RandomForestRegressionModel (eg, after doing a grid search)
It is possible to call
{{regressor._java_obj.getMaxDepth()}}
but most other decision trees allow
{{regressor.getMaxDepth()}}
> RandomForestRegressionModel should expose getMaxDepth in R
> ----------------------------------------------------------
>
> Key: SPARK-19282
> URL: https://issues.apache.org/jira/browse/SPARK-19282
> Project: Spark
> Issue Type: Improvement
> Components: ML, SparkR
> Affects Versions: 2.1.0
> Reporter: Nick Lothian
> Assignee: Xin Ren
> Priority: Minor
>
> Currently it isn't clear hot to get the max depth of a
> RandomForestRegressionModel (eg, after doing a grid search)
> It is possible to call
> {{regressor._java_obj.getMaxDepth()}}
> but most other decision trees allow
> {{regressor.getMaxDepth()}}
> UPDATE: This is just for Spark R. SEe [SPARK-20498] for Python.
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