fixed off-by-one error in bin to split conversion

Author: manishamde

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

@@ -1012,7 +1012,7 @@ object DecisionTree extends Serializable with Logging {
               = binData(shift + numClasses * splitIndex + innerClassIndex) +
                 leftNodeAgg(featureIndex)(splitIndex - 1)(innerClassIndex)
             rightNodeAgg(featureIndex)(numBins - 2 - splitIndex)(innerClassIndex) =
-              binData(shift + (numClasses * (numBins - 2 - splitIndex) + innerClassIndex)) +
+              binData(shift + (numClasses * (numBins - 1 - splitIndex) + innerClassIndex)) +
                 rightNodeAgg(featureIndex)(numBins - 1 - splitIndex)(innerClassIndex)
             innerClassIndex += 1
           }
@@ -1077,13 +1077,13 @@ object DecisionTree extends Serializable with Logging {
           // calculating right node aggregate for a split as a sum of right node aggregate of a
           // higher split and the right bin aggregate of a bin where the split is a low split
           rightNodeAgg(featureIndex)(numBins - 2 - splitIndex)(0) =
-            binData(shift + (3 * (numBins - 2 - splitIndex))) +
+            binData(shift + (3 * (numBins - 1 - splitIndex))) +
               rightNodeAgg(featureIndex)(numBins - 1 - splitIndex)(0)
           rightNodeAgg(featureIndex)(numBins - 2 - splitIndex)(1) =
-            binData(shift + (3 * (numBins - 2 - splitIndex) + 1)) +
+            binData(shift + (3 * (numBins - 1 - splitIndex) + 1)) +
               rightNodeAgg(featureIndex)(numBins - 1 - splitIndex)(1)
           rightNodeAgg(featureIndex)(numBins - 2 - splitIndex)(2) =
-            binData(shift + (3 * (numBins - 2 - splitIndex) + 2)) +
+            binData(shift + (3 * (numBins - 1 - splitIndex) + 2)) +
               rightNodeAgg(featureIndex)(numBins - 1 - splitIndex)(2)
 
           splitIndex += 1

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

@@ -412,9 +412,8 @@ class DecisionTreeSuite extends FunSuite with LocalSparkContext {
 
     val stats = bestSplits(0)._2
     assert(stats.gain > 0)
-    assert(stats.predict === 0)
-    assert(stats.prob > 0.5)
-    assert(stats.prob < 0.6)
+    assert(stats.predict === 1)
+    assert(stats.prob == 0.6)
     assert(stats.impurity > 0.2)
   }
 
@@ -440,8 +439,7 @@ class DecisionTreeSuite extends FunSuite with LocalSparkContext {
 
     val stats = bestSplits(0)._2
     assert(stats.gain > 0)
-    assert(stats.predict > 0.4)
-    assert(stats.predict < 0.5)
+    assert(stats.predict == 0.6)
     assert(stats.impurity > 0.2)
   }
 
@@ -657,7 +655,6 @@ class DecisionTreeSuite extends FunSuite with LocalSparkContext {
     val bestSplit = bestSplits(0)._1
     assert(bestSplit.feature === 0)
     assert(bestSplit.categories.length === 1)
-    println(bestSplit)
     assert(bestSplit.categories.contains(1.0))
     assert(bestSplit.featureType === Categorical)
   }