diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala
index 952f03f10e538..a5a4e61049ccf 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala
@@ -60,7 +60,7 @@ class DecisionTree (private val strategy: Strategy) extends Serializable with Lo
     // depth of the decision tree
     val maxDepth = strategy.maxDepth
     // the max number of nodes possible given the depth of the tree
-    val maxNumNodes = scala.math.pow(2, maxDepth).toInt - 1
+    val maxNumNodes = math.pow(2, maxDepth).toInt - 1
     // Initialize an array to hold filters applied to points for each node.
     val filters = new Array[List[Filter]](maxNumNodes)
     // The filter at the top node is an empty list.
@@ -85,11 +85,11 @@ class DecisionTree (private val strategy: Strategy) extends Serializable with Lo
     }
     logDebug("numElementsPerNode = " + numElementsPerNode)
     val arraySizePerNode = 8 * numElementsPerNode // approx. memory usage for bin aggregate array
-    val maxNumberOfNodesPerGroup = scala.math.max(maxMemoryUsage / arraySizePerNode, 1)
+    val maxNumberOfNodesPerGroup = math.max(maxMemoryUsage / arraySizePerNode, 1)
     logDebug("maxNumberOfNodesPerGroup = " + maxNumberOfNodesPerGroup)
     // nodes at a level is 2^(level-1). level is zero indexed.
-    val maxLevelForSingleGroup = scala.math.max(
-      (scala.math.log(maxNumberOfNodesPerGroup) / scala.math.log(2)).floor.toInt - 1, 0)
+    val maxLevelForSingleGroup = math.max(
+      (math.log(maxNumberOfNodesPerGroup) / math.log(2)).floor.toInt - 1, 0)
     logDebug("max level for single group = " + maxLevelForSingleGroup)
 
     /*
@@ -120,7 +120,7 @@ class DecisionTree (private val strategy: Strategy) extends Serializable with Lo
           filters)
         logDebug("final best split = " + nodeSplitStats._1)
       }
-      require(scala.math.pow(2, level) == splitsStatsForLevel.length)
+      require(math.pow(2, level) == splitsStatsForLevel.length)
       // Check whether all the nodes at the current level at leaves.
       val allLeaf = splitsStatsForLevel.forall(_._2.gain <= 0)
       logDebug("all leaf = " + allLeaf)
@@ -153,7 +153,7 @@ class DecisionTree (private val strategy: Strategy) extends Serializable with Lo
       nodes: Array[Node]): Unit = {
     val split = nodeSplitStats._1
     val stats = nodeSplitStats._2
-    val nodeIndex = scala.math.pow(2, level).toInt - 1 + index
+    val nodeIndex = math.pow(2, level).toInt - 1 + index
     val isLeaf = (stats.gain <= 0) || (level == strategy.maxDepth - 1)
     val node = new Node(nodeIndex, stats.predict, isLeaf, Some(split), None, None, Some(stats))
     logDebug("Node = " + node)
@@ -174,7 +174,7 @@ class DecisionTree (private val strategy: Strategy) extends Serializable with Lo
     var i = 0
     while (i <= 1) {
      // Calculate the index of the node from the node level and the index at the current level.
-      val nodeIndex = scala.math.pow(2, level + 1).toInt - 1 + 2 * index + i
+      val nodeIndex = math.pow(2, level + 1).toInt - 1 + 2 * index + i
       if (level < maxDepth - 1) {
         val impurity = if (i == 0) {
           nodeSplitStats._2.leftImpurity
@@ -300,7 +300,7 @@ object DecisionTree extends Serializable with Logging {
       maxLevelForSingleGroup: Int): Array[(Split, InformationGainStats)] = {
     // split into groups to avoid memory overflow during aggregation
     if (level >  maxLevelForSingleGroup) {
-      val numGroups = scala.math.pow(2, (level - maxLevelForSingleGroup)).toInt
+      val numGroups = math.pow(2, (level - maxLevelForSingleGroup)).toInt
       logDebug("numGroups = " + numGroups)
       var groupIndex = 0
       var bestSplits = new Array[(Split, InformationGainStats)](0)
@@ -366,7 +366,7 @@ object DecisionTree extends Serializable with Logging {
      */
 
     // common calculations for multiple nested methods
-    val numNodes = scala.math.pow(2, level).toInt / numGroups
+    val numNodes = math.pow(2, level).toInt / numGroups
     logDebug("numNodes = " + numNodes)
     // Find the number of features by looking at the first sample.
     val numFeatures = input.first().features.size
@@ -382,7 +382,7 @@ object DecisionTree extends Serializable with Logging {
       if (level == 0) {
         List[Filter]()
       } else {
-        val nodeFilterIndex = scala.math.pow(2, level).toInt - 1 + nodeIndex + groupShift
+        val nodeFilterIndex = math.pow(2, level).toInt - 1 + nodeIndex + groupShift
         filters(nodeFilterIndex)
       }
     }
@@ -951,7 +951,7 @@ object DecisionTree extends Serializable with Logging {
     // Iterating over all nodes at this level
     var node = 0
     while (node < numNodes) {
-      val nodeImpurityIndex = scala.math.pow(2, level).toInt - 1 + node + groupShift
+      val nodeImpurityIndex = math.pow(2, level).toInt - 1 + node + groupShift
       val binsForNode: Array[Double] = getBinDataForNode(node)
       logDebug("nodeImpurityIndex = " + nodeImpurityIndex)
       val parentNodeImpurity = parentImpurities(nodeImpurityIndex)