implementing code style suggestions

Author: manishamde

mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala

@@ -245,7 +245,7 @@ object DecisionTree extends Serializable with Logging {
     new DecisionTree(strategy).train(input: RDD[LabeledPoint])
   }
 
-  val InvalidBinIndex = -1
+  private val InvalidBinIndex = -1
 
   /**
    * Returns an array of optimal splits for all nodes at a given level

mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Entropy.scala

@@ -17,7 +17,7 @@
 
 package org.apache.spark.mllib.tree.impurity
 
-import javax.naming.OperationNotSupportedException
+import java.lang.UnsupportedOperationException
 
 /**
  * Class for calculating [[http://en.wikipedia.org/wiki/Binary_entropy_function entropy]] during
@@ -45,5 +45,5 @@ object Entropy extends Impurity {
    }
 
   def calculate(count: Double, sum: Double, sumSquares: Double): Double =
-    throw new OperationNotSupportedException("Entropy.calculate")
+    throw new UnsupportedOperationException("Entropy.calculate")
 }

mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Gini.scala

@@ -17,11 +17,11 @@
 
 package org.apache.spark.mllib.tree.impurity
 
-import javax.naming.OperationNotSupportedException
+import java.lang.UnsupportedOperationException
 
 /**
- * Class for calculating the [[http://en.wikipedia.org/wiki/Gini_coefficient Gini
- * coefficent]] during binary classification
+ * Class for calculating the [[http://en.wikipedia
+ * .org/wiki/Decision_tree_learning#Gini_impurity]] during binary classification
  */
 object Gini extends Impurity {
 
@@ -43,6 +43,6 @@ object Gini extends Impurity {
   }
 
   def calculate(count: Double, sum: Double, sumSquares: Double): Double =
-    throw new OperationNotSupportedException("Gini.calculate")
+    throw new UnsupportedOperationException("Gini.calculate")
 
 }

mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Variance.scala

@@ -17,15 +17,14 @@
 
 package org.apache.spark.mllib.tree.impurity
 
-import javax.naming.OperationNotSupportedException
-import org.apache.spark.Logging
+import java.lang.UnsupportedOperationException
 
 /**
  * Class for calculating variance during regression
  */
-object Variance extends Impurity with Logging {
+object Variance extends Impurity {
    def calculate(c0: Double, c1: Double): Double
-   = throw new OperationNotSupportedException("Variance.calculate")
+   = throw new UnsupportedOperationException("Variance.calculate")
 
   /**
    * variance calculation

mllib/src/main/scala/org/apache/spark/mllib/tree/model/Node.scala

@@ -18,7 +18,6 @@
 package org.apache.spark.mllib.tree.model
 
 import org.apache.spark.Logging
-import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.mllib.tree.configuration.FeatureType._
 
 /**

mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala

@@ -17,22 +17,15 @@
 
 package org.apache.spark.mllib.tree
 
-import scala.util.Random
-
 import org.scalatest.BeforeAndAfterAll
 import org.scalatest.FunSuite
 
 import org.apache.spark.SparkContext
-import org.apache.spark.SparkContext._
-
-import org.jblas._
-import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.mllib.tree.impurity.{Entropy, Gini, Variance}
 import org.apache.spark.mllib.tree.model.Filter
 import org.apache.spark.mllib.tree.configuration.Strategy
 import org.apache.spark.mllib.tree.configuration.Algo._
-import scala.collection.mutable
 import org.apache.spark.mllib.tree.configuration.FeatureType._
 
 class DecisionTreeSuite extends FunSuite with BeforeAndAfterAll {