Added topNode doc in DecisionTree and scalastyle fix

Author: jkbradley

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

@@ -359,6 +359,7 @@ object DecisionTree extends Serializable with Logging {
    * @param input Training data: RDD of [[org.apache.spark.mllib.tree.impl.TreePoint]]
    * @param metadata Learning and dataset metadata
    * @param level Level of the tree
+   * @param topNode Root node of the tree (or invalid node when training first level).
    * @param splits possible splits for all features, indexed (numFeatures)(numSplits)
    * @param bins possible bins for all features, indexed (numFeatures)(numBins)
    * @param maxLevelForSingleGroup the deepest level for single-group level-wise computation.

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

@@ -270,8 +270,8 @@ class DecisionTreeSuite extends FunSuite with LocalSparkContext {
     assert(bins(0).length === 0)
 
     val treeInput = TreePoint.convertToTreeRDD(rdd, bins, metadata)
-    val (rootNode: Node, doneTraining: Boolean) = DecisionTree.findBestSplits(treeInput, metadata, 0,
-      null, splits, bins, 10)
+    val (rootNode: Node, doneTraining: Boolean) =
+      DecisionTree.findBestSplits(treeInput, metadata, 0, null, splits, bins, 10)
 
     val split = rootNode.split.get
     assert(split.categories === List(1.0))