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https://issues.apache.org/jira/browse/SPARK-29232?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-29232:
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Priority: Major (was: Critical)
> RandomForestRegressionModel does not update the parameter maps of the
> DecisionTreeRegressionModels underneath
> -------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-29232
> URL: https://issues.apache.org/jira/browse/SPARK-29232
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.4.0
> Reporter: Jiaqi Guo
> Priority: Major
>
> We trained a RandomForestRegressionModel, and tried to access the trees. Even
> though the DecisionTreeRegressionModel is correctly built with the proper
> parameters from random forest, the parameter map is not updated, and still
> contains only the default value.
> For example, if a RandomForestRegressor was trained with maxDepth of 12, then
> accessing the tree information, extractParamMap still returns the default
> values, with maxDepth=5. Calling the depth itself of
> DecisionTreeRegressionModel returns the correct value of 12 though.
> This creates issues when we want to access each individual tree and build the
> trees back up for the random forest estimator.
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