change private and lazy

Author: wangmiao1981

mllib/src/main/scala/org/apache/spark/ml/r/LogisticRegressionWrapper.scala

@@ -40,13 +40,13 @@ private[r] class LogisticRegressionWrapper private (
   private val lrModel: LogisticRegressionModel =
     pipeline.stages(1).asInstanceOf[LogisticRegressionModel]
 
-  val rFeatures: Array[String] = if (lrModel.getFitIntercept) {
+  lazy val rFeatures: Array[String] = if (lrModel.getFitIntercept) {
     Array("(Intercept)") ++ features
   } else {
     features
   }
 
-  val rCoefficients: Array[Double] = {
+  lazy val rCoefficients: Array[Double] = {
     val numRows = lrModel.coefficientMatrix.numRows
     val numCols = lrModel.coefficientMatrix.numCols
     val numColsWithIntercept = if (lrModel.getFitIntercept) numCols + 1 else numCols

mllib/src/main/scala/org/apache/spark/ml/r/MultilayerPerceptronClassifierWrapper.scala

@@ -36,11 +36,11 @@ private[r] class MultilayerPerceptronClassifierWrapper private (
 
   import MultilayerPerceptronClassifierWrapper._
 
-  val mlpModel: MultilayerPerceptronClassificationModel =
+  private val mlpModel: MultilayerPerceptronClassificationModel =
     pipeline.stages(1).asInstanceOf[MultilayerPerceptronClassificationModel]
 
-  val weights: Array[Double] = mlpModel.weights.toArray
-  val layers: Array[Int] = mlpModel.layers
+  lazy val weights: Array[Double] = mlpModel.weights.toArray
+  lazy val layers: Array[Int] = mlpModel.layers
 
   def transform(dataset: Dataset[_]): DataFrame = {
     pipeline.transform(dataset)