diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/NaiveBayesExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/NaiveBayesExample.scala
index 0187ad603a65..154fa07fc825 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/NaiveBayesExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/NaiveBayesExample.scala
@@ -15,6 +15,16 @@
  * limitations under the License.
  */
 
+/*
+ * Usage:
+ *
+ *  sbt package
+ *
+ *  spark-submit --class "org.apache.spark.examples.mllib.NaiveBayesExample"
+ *    --master local[4]
+ *    examples/target/scala-2.11/spark-examples_2.11-2.0.0-SNAPSHOT.jar
+ */
+
 // scalastyle:off println
 package org.apache.spark.examples.mllib
 
@@ -23,6 +33,9 @@ import org.apache.spark.{SparkConf, SparkContext}
 import org.apache.spark.mllib.classification.{NaiveBayes, NaiveBayesModel}
 import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.regression.LabeledPoint
+
+import java.io.File;
+import org.apache.commons.io.FileUtils;
 // $example off$
 
 object NaiveBayesExample {
@@ -46,10 +59,18 @@ object NaiveBayesExample {
 
     val predictionAndLabel = test.map(p => (model.predict(p.features), p.label))
     val accuracy = 1.0 * predictionAndLabel.filter(x => x._1 == x._2).count() / test.count()
+    println("model accuracy %f".format(accuracy))
 
     // Save and load model
-    model.save(sc, "target/tmp/myNaiveBayesModel")
-    val sameModel = NaiveBayesModel.load(sc, "target/tmp/myNaiveBayesModel")
+    val outputDir = "target/tmp/myNaiveBayesModel"
+    FileUtils.forceDelete(new File(outputDir))
+    model.save(sc, outputDir)
+    val sameModel = NaiveBayesModel.load(sc, outputDir)
+
+    val samePredictionAndLabel = test.map(p => (sameModel.predict(p.features), p.label))
+    val sameAccuracy = 1.0 * samePredictionAndLabel.filter(x => x._1 == x._2).count() /
+        test.count()
+    println("sameModel accuracy %f".format(sameAccuracy))
     // $example off$
   }
 }