[jira] [Commented] (SPARK-19282) RandomForestRegressionModel should expose getMaxDepth

["Bryan Cutler (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-19282?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15848963#comment-15848963 ] 

Bryan Cutler commented on SPARK-19282:
--------------------------------------

Is this another case of SPARK-10931?  The PySpark ML models generally do not copy over parameters from the wrapped Java object, so many of the functions to get those params are missing.  That issue will need to be resolved first.

> RandomForestRegressionModel should expose getMaxDepth
> -----------------------------------------------------
>
>                 Key: SPARK-19282
>                 URL: https://issues.apache.org/jira/browse/SPARK-19282
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.1.0
>            Reporter: Nick Lothian
>            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()}} 



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