merged with upstream master

mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala

@@ -17,6 +17,10 @@
 
 package org.apache.spark.mllib.classification
 
+import java.lang.{Iterable => JIterable}
+
+import scala.collection.JavaConverters._
+
 import breeze.linalg.{DenseMatrix => BDM, DenseVector => BDV, argmax => brzArgmax, sum => brzSum, Axis}
 import breeze.numerics.{exp => brzExp, log => brzLog}
 
@@ -203,12 +207,16 @@ class NaiveBayes private (
     this
   }
 
+  /** Get the smoothing parameter. */
+  def getLambda: Double = lambda
+
   /** Set the model type. Default: Multinomial. */
   def setModelType(model: NaiveBayes.ModelType): NaiveBayes = {
     this.modelType = model
     this
   }
 
+  /** Get the model type. */
   def getModelType: NaiveBayes.ModelType = this.modelType
 
   /**

mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala

@@ -108,6 +108,14 @@ class NaiveBayesSuite extends FunSuite with MLlibTestSparkContext {
     }
   }
 
+  test("get, set params") {
+    val nb = new NaiveBayes()
+    nb.setLambda(2.0)
+    assert(nb.getLambda === 2.0)
+    nb.setLambda(3.0)
+    assert(nb.getLambda === 3.0)
+  }
+
   test("Naive Bayes Multinomial") {
     val nPoints = 1000
     val pi = Array(0.5, 0.1, 0.4).map(math.log)