[SPARK-9756] [ML] Make constructors in ML decision trees private

These should be made private until there is a public constructor for providing `rootNode: Node` to use these constructors.

jkbradley

Author: Feynman Liang <fliang@databricks.com>

Closes #8046 from feynmanliang/SPARK-9756 and squashes the following commits:

2cbdf08 [Feynman Liang] Make RFRegressionModel aux constructor private
a06f596 [Feynman Liang] Make constructors in ML decision trees private

mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala

@@ -117,7 +117,7 @@ final class DecisionTreeClassificationModel private[ml] (
    * Construct a decision tree classification model.
    * @param rootNode  Root node of tree, with other nodes attached.
    */
-  def this(rootNode: Node, numClasses: Int) =
+  private[ml] def this(rootNode: Node, numClasses: Int) =
     this(Identifiable.randomUID("dtc"), rootNode, numClasses)
 
   override protected def predict(features: Vector): Double = {

mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala

@@ -136,7 +136,10 @@ final class RandomForestClassificationModel private[ml] (
    * Construct a random forest classification model, with all trees weighted equally.
    * @param trees  Component trees
    */
-  def this(trees: Array[DecisionTreeClassificationModel], numFeatures: Int, numClasses: Int) =
+  private[ml] def this(
+      trees: Array[DecisionTreeClassificationModel],
+      numFeatures: Int,
+      numClasses: Int) =
     this(Identifiable.randomUID("rfc"), trees, numFeatures, numClasses)
 
   override def trees: Array[DecisionTreeModel] = _trees.asInstanceOf[Array[DecisionTreeModel]]

mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala

@@ -107,7 +107,7 @@ final class DecisionTreeRegressionModel private[ml] (
    * Construct a decision tree regression model.
    * @param rootNode  Root node of tree, with other nodes attached.
    */
-  def this(rootNode: Node) = this(Identifiable.randomUID("dtr"), rootNode)
+  private[ml] def this(rootNode: Node) = this(Identifiable.randomUID("dtr"), rootNode)
 
   override protected def predict(features: Vector): Double = {
     rootNode.predictImpl(features).prediction

mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala

@@ -125,7 +125,7 @@ final class RandomForestRegressionModel private[ml] (
    * Construct a random forest regression model, with all trees weighted equally.
    * @param trees  Component trees
    */
-  def this(trees: Array[DecisionTreeRegressionModel], numFeatures: Int) =
+  private[ml] def this(trees: Array[DecisionTreeRegressionModel], numFeatures: Int) =
     this(Identifiable.randomUID("rfr"), trees, numFeatures)
 
   override def trees: Array[DecisionTreeModel] = _trees.asInstanceOf[Array[DecisionTreeModel]]