Updating ML Doc "Estimator, Transformer, and Param" example to use model.extractParamMap instead of model.fittingParamMap, which no longer exists.

Author: dusenberrymw

docs/ml-guide.md

@@ -207,7 +207,7 @@ val model1 = lr.fit(training.toDF)
 // we can view the parameters it used during fit().
 // This prints the parameter (name: value) pairs, where names are unique IDs for this
 // LogisticRegression instance.
-println("Model 1 was fit using parameters: " + model1.fittingParamMap)
+println("Model 1 was fit using parameters: " + model1.extractParamMap)
 
 // We may alternatively specify parameters using a ParamMap,
 // which supports several methods for specifying parameters.
@@ -222,7 +222,7 @@ val paramMapCombined = paramMap ++ paramMap2
 // Now learn a new model using the paramMapCombined parameters.
 // paramMapCombined overrides all parameters set earlier via lr.set* methods.
 val model2 = lr.fit(training.toDF, paramMapCombined)
-println("Model 2 was fit using parameters: " + model2.fittingParamMap)
+println("Model 2 was fit using parameters: " + model2.extractParamMap)
 
 // Prepare test data.
 val test = sc.parallelize(Seq(