remove numBins field in the Strategy class

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

@@ -56,9 +56,6 @@ class DecisionTree private(val strategy: Strategy) extends Serializable with Log
     val (splits, bins) = DecisionTree.findSplitsBins(input, strategy)
     logDebug("numSplits = " + bins(0).length)
 
-    // Set number of bins for the input data.
-    strategy.numBins = bins(0).length
-
     // depth of the decision tree
     val maxDepth = strategy.maxDepth
     // the max number of nodes possible given the depth of the tree
@@ -300,7 +297,7 @@ object DecisionTree extends Serializable with Logging {
     // Find the number of features by looking at the first sample.
     val numFeatures = input.first().features.length
     logDebug("numFeatures = " + numFeatures)
-    val numBins = strategy.numBins
+    val numBins = bins(0).length
     logDebug("numBins = " + numBins)
 
     /** Find the filters used before reaching the current code. */

mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala

@@ -40,7 +40,4 @@ class Strategy (
     val maxDepth: Int,
     val maxBins: Int = 100,
     val quantileCalculationStrategy: QuantileStrategy = Sort,
-    val categoricalFeaturesInfo: Map[Int,Int] = Map[Int,Int]()) extends Serializable {
-
-  var numBins: Int  = Int.MinValue
-}
+    val categoricalFeaturesInfo: Map[Int,Int] = Map[Int,Int]()) extends Serializable

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

@@ -252,7 +252,6 @@ class DecisionTreeSuite extends FunSuite with BeforeAndAfterAll {
       maxBins = 100,
       categoricalFeaturesInfo = Map(0 -> 3, 1-> 3))
     val (splits, bins) = DecisionTree.findSplitsBins(rdd, strategy)
-    strategy.numBins = 100
     val bestSplits = DecisionTree.findBestSplits(rdd, new Array(7), strategy, 0,
       Array[List[Filter]](), splits, bins)
 
@@ -280,7 +279,6 @@ class DecisionTreeSuite extends FunSuite with BeforeAndAfterAll {
       maxBins = 100,
       categoricalFeaturesInfo = Map(0 -> 3, 1-> 3))
     val (splits, bins) = DecisionTree.findSplitsBins(rdd,strategy)
-    strategy.numBins = 100
     val bestSplits = DecisionTree.findBestSplits(rdd, new Array(7), strategy, 0,
       Array[List[Filter]](), splits, bins)
 
@@ -310,7 +308,6 @@ class DecisionTreeSuite extends FunSuite with BeforeAndAfterAll {
     assert(splits(0).length === 99)
     assert(bins(0).length === 100)
 
-    strategy.numBins = 100
     val bestSplits = DecisionTree.findBestSplits(rdd, new Array(7), strategy, 0,
       Array[List[Filter]](), splits, bins)
     assert(bestSplits.length === 1)
@@ -334,7 +331,6 @@ class DecisionTreeSuite extends FunSuite with BeforeAndAfterAll {
     assert(splits(0).length === 99)
     assert(bins(0).length === 100)
 
-    strategy.numBins = 100
     val bestSplits = DecisionTree.findBestSplits(rdd, Array(0.0), strategy, 0,
       Array[List[Filter]](), splits, bins)
     assert(bestSplits.length === 1)
@@ -359,7 +355,6 @@ class DecisionTreeSuite extends FunSuite with BeforeAndAfterAll {
     assert(splits(0).length === 99)
     assert(bins(0).length === 100)
 
-    strategy.numBins = 100
     val bestSplits = DecisionTree.findBestSplits(rdd, Array(0.0), strategy, 0,
       Array[List[Filter]](), splits, bins)
     assert(bestSplits.length === 1)
@@ -384,7 +379,6 @@ class DecisionTreeSuite extends FunSuite with BeforeAndAfterAll {
     assert(splits(0).length === 99)
     assert(bins(0).length === 100)
 
-    strategy.numBins = 100
     val bestSplits = DecisionTree.findBestSplits(rdd, Array(0.0), strategy, 0,
       Array[List[Filter]](), splits, bins)
     assert(bestSplits.length === 1)