diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
index b11fd4f128c56..2ebc7fa5d4234 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
@@ -166,6 +166,9 @@ class NaiveBayes private (private var lambda: Double) extends Serializable with
     this
   }
 
+  /** Get the smoothing parameter. Default: 1.0. */
+  def getLambda: Double = lambda
+
   /**
    * Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.
    *
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
index 64dcc0fb9f82c..5a27c7d2309c5 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
@@ -85,6 +85,14 @@ class NaiveBayesSuite extends FunSuite with MLlibTestSparkContext {
     assert(numOfPredictions < input.length / 5)
   }
 
+  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") {
     val nPoints = 10000