Model 1 and Model 2 ParamMaps Missing

@dongjoon-hyun @HyukjinKwon

Error in PySpark example code:
[https://github.com/apache/spark/blob/master/examples/src/main/python/ml/estimator_transformer_param_example.py]

The original Scala code says
println("Model 2 was fit using parameters: " + model2.parent.extractParamMap)

The parent is lr

There is no method for accessing parent as is done in Scala.

This code has been tested in Python, and returns values consistent with Scala

examples/src/main/python/ml/estimator_transformer_param_example.py

@@ -53,7 +53,7 @@
     # This prints the parameter (name: value) pairs, where names are unique IDs for this
     # LogisticRegression instance.
     print("Model 1 was fit using parameters: ")
-    print(model1.extractParamMap())
+    print(lr.extractParamMap())
 
     # We may alternatively specify parameters using a Python dictionary as a paramMap
     paramMap = {lr.maxIter: 20}
@@ -69,7 +69,7 @@
     # paramMapCombined overrides all parameters set earlier via lr.set* methods.
     model2 = lr.fit(training, paramMapCombined)
     print("Model 2 was fit using parameters: ")
-    print(model2.extractParamMap())
+    print(lr.extractParamMap(extra=paramMapCombined))
 
     # Prepare test data
     test = spark.createDataFrame([