[SPARK-15092][SPARK-15139][PYSPARK][ML] Pyspark TreeEnsemble missing methods

## What changes were proposed in this pull request?

Add `toDebugString` and `totalNumNodes` to `TreeEnsembleModels` and add `toDebugString` to `DecisionTreeModel`

## How was this patch tested?

Extended doc tests.

Author: Holden Karau <holden@us.ibm.com>

Closes #12919 from holdenk/SPARK-15139-pyspark-treeEnsemble-missing-methods.

1 files changed, 47 insertions, 1 deletions

diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py
index 1b7af7ef59..7c79ab73c7 100644
--- a/python/pyspark/ml/regression.py
+++ b/python/pyspark/ml/regression.py
@@ -593,7 +593,7 @@ class RandomForestParams(TreeEnsembleParams):
     featureSubsetStrategy = \
         Param(Params._dummy(), "featureSubsetStrategy",
               "The number of features to consider for splits at each tree node. Supported " +
-              "options: " + ", ".join(supportedFeatureSubsetStrategies),
+              "options: " + ", ".join(supportedFeatureSubsetStrategies) + " (0.0-1.0], [1-n].",
               typeConverter=TypeConverters.toString)
 
     def __init__(self):
@@ -744,6 +744,12 @@ class DecisionTreeModel(JavaModel):
         """Return depth of the decision tree."""
         return self._call_java("depth")
 
+    @property
+    @since("2.0.0")
+    def toDebugString(self):
+        """Full description of model."""
+        return self._call_java("toDebugString")
+
     def __repr__(self):
         return self._call_java("toString")
 
@@ -759,11 +765,35 @@ class TreeEnsembleModels(JavaModel):
     """
 
     @property
+    @since("2.0.0")
+    def trees(self):
+        """Trees in this ensemble. Warning: These have null parent Estimators."""
+        return [DecisionTreeModel(m) for m in list(self._call_java("trees"))]
+
+    @property
+    @since("2.0.0")
+    def getNumTrees(self):
+        """Number of trees in ensemble."""
+        return self._call_java("getNumTrees")
+
+    @property
     @since("1.5.0")
     def treeWeights(self):
         """Return the weights for each tree"""
         return list(self._call_java("javaTreeWeights"))
 
+    @property
+    @since("2.0.0")
+    def totalNumNodes(self):
+        """Total number of nodes, summed over all trees in the ensemble."""
+        return self._call_java("totalNumNodes")
+
+    @property
+    @since("2.0.0")
+    def toDebugString(self):
+        """Full description of model."""
+        return self._call_java("toDebugString")
+
     def __repr__(self):
         return self._call_java("toString")
 
@@ -825,6 +855,10 @@ class RandomForestRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi
     >>> test0 = spark.createDataFrame([(Vectors.dense(-1.0),)], ["features"])
     >>> model.transform(test0).head().prediction
     0.0
+    >>> model.trees
+    [DecisionTreeRegressionModel (uid=...) of depth..., DecisionTreeRegressionModel...]
+    >>> model.getNumTrees
+    2
     >>> test1 = spark.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"])
     >>> model.transform(test1).head().prediction
     0.5
@@ -898,6 +932,12 @@ class RandomForestRegressionModel(TreeEnsembleModels, JavaMLWritable, JavaMLRead
 
     @property
     @since("2.0.0")
+    def trees(self):
+        """Trees in this ensemble. Warning: These have null parent Estimators."""
+        return [DecisionTreeRegressionModel(m) for m in list(self._call_java("trees"))]
+
+    @property
+    @since("2.0.0")
     def featureImportances(self):
         """
         Estimate of the importance of each feature.
@@ -1045,6 +1085,12 @@ class GBTRegressionModel(TreeEnsembleModels, JavaMLWritable, JavaMLReadable):
         """
         return self._call_java("featureImportances")
 
+    @property
+    @since("2.0.0")
+    def trees(self):
+        """Trees in this ensemble. Warning: These have null parent Estimators."""
+        return [DecisionTreeRegressionModel(m) for m in list(self._call_java("trees"))]
+
 
 @inherit_doc
 class AFTSurvivalRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol,