put back in constructor for NaiveBayes

Author: leahmcguire

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

@@ -186,6 +186,8 @@ class NaiveBayes private (
     private var lambda: Double,
     private var modelType: NaiveBayes.ModelType) extends Serializable with Logging {
 
+  private def this(lambda: Double) = this(lambda, NaiveBayes.Multinomial)
+
   def this() = this(1.0, NaiveBayes.Multinomial)
 
   /** Set the smoothing parameter. Default: 1.0. */

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

@@ -146,23 +146,15 @@ class NaiveBayesSuite extends FunSuite with MLlibTestSparkContext {
     ).map(_.map(math.log))
 
     val testData = NaiveBayesSuite.generateNaiveBayesInput(
-      pi,
-      theta,
-      nPoints,
-      45,
-      NaiveBayes.Bernoulli)
+      pi, theta, nPoints, 45, NaiveBayes.Bernoulli)
     val testRDD = sc.parallelize(testData, 2)
     testRDD.cache()
 
     val model = NaiveBayes.train(testRDD, 1.0, "bernoulli")
     validateModelFit(pi, theta, model)
 
     val validationData = NaiveBayesSuite.generateNaiveBayesInput(
-      pi,
-      theta,
-      nPoints,
-      20,
-      NaiveBayes.Bernoulli)
+      pi, theta, nPoints, 20, NaiveBayes.Bernoulli)
     val validationRDD = sc.parallelize(validationData, 2)
 
     // Test prediction on RDD.