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https://issues.apache.org/jira/browse/SPARK-19282?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15924644#comment-15924644
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Bryan Cutler commented on SPARK-19282:
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This is common issue with all PySpark ML Models and SPARK-10931 should be
completed first, then probably a coordinated effort to expose all parameters
from Models which most likely means using a common base class between the
estimator and model that contains the params and get methods.
> RandomForestRegressionModel summary should expose getMaxDepth
> -------------------------------------------------------------
>
> Key: SPARK-19282
> URL: https://issues.apache.org/jira/browse/SPARK-19282
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark, SparkR
> Affects Versions: 2.1.0
> Reporter: Nick Lothian
> Assignee: Xin Ren
> Priority: Minor
> Fix For: 2.2.0
>
>
> 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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