[SPARK-15113][PYSPARK][ML] Add missing num features num classes

## What changes were proposed in this pull request?

Add missing `numFeatures` and `numClasses` to the wrapped Java models in PySpark ML pipelines. Also tag `DecisionTreeClassificationModel` as Expiremental to match Scala doc.

## How was this patch tested?

Extended doctests

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

Closes #12889 from holdenk/SPARK-15113-add-missing-numFeatures-numClasses.

1 files changed, 16 insertions, 0 deletions

diff --git a/python/pyspark/ml/util.py b/python/pyspark/ml/util.py
index 4a31a29809..7d39c30122 100644
--- a/python/pyspark/ml/util.py
+++ b/python/pyspark/ml/util.py
@@ -238,3 +238,19 @@ class JavaMLReadable(MLReadable):
     def read(cls):
         """Returns an MLReader instance for this class."""
         return JavaMLReader(cls)
+
+
+@inherit_doc
+class JavaPredictionModel():
+    """
+    (Private) Java Model for prediction tasks (regression and classification).
+    To be mixed in with class:`pyspark.ml.JavaModel`
+    """
+
+    @property
+    @since("2.1.0")
+    def numFeatures(self):
+        """
+        Returns the number of features the model was trained on. If unknown, returns -1
+        """
+        return self._call_java("numFeatures")