[SPARK-7833] [ML] Add python wrapper for RegressionEvaluator

Author: Ram Sriharsha <rsriharsha@hw11853.local>

Closes #6365 from harsha2010/SPARK-7833 and squashes the following commits:

923f288 [Ram Sriharsha] cleanup
7623b7d [Ram Sriharsha] python style fix
9743f83 [Ram Sriharsha] [SPARK-7833][ml] Add python wrapper for RegressionEvaluator

2 files changed, 3 insertions, 2 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
index ec493f8f1b..80458928c5 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
@@ -31,14 +31,14 @@ import org.apache.spark.sql.types.DoubleType
  * Evaluator for regression, which expects two input columns: prediction and label.
  */
 @AlphaComponent
-class RegressionEvaluator(override val uid: String)
+final class RegressionEvaluator(override val uid: String)
   extends Evaluator with HasPredictionCol with HasLabelCol {
 
   def this() = this(Identifiable.randomUID("regEval"))
 
   /**
    * param for metric name in evaluation
-   * @group param
+   * @group param supports mse, rmse, r2, mae as valid metric names.
    */
   val metricName: Param[String] = {
     val allowedParams = ParamValidators.inArray(Array("mse", "rmse", "r2", "mae"))
diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala
index 983f8b460b..3ea7aad527 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala
@@ -39,6 +39,7 @@ class RegressionEvaluatorSuite extends FunSuite with MLlibTestSparkContext {
     val dataset = sqlContext.createDataFrame(
       sc.parallelize(LinearDataGenerator.generateLinearInput(
         6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2))
+    
     /**
      * Using the following R code to load the data, train the model and evaluate metrics.
      *