SPARK-5020 [MLlib] GaussianMixtureModel.predictMembership() should take an RDD only

Removed unnecessary parameters to predictMembership()

CC: jkbradley

Author: Travis Galoppo <tjg2107@columbia.edu>

Closes #3854 from tgaloppo/spark-5020 and squashes the following commits:

1bf4669 [Travis Galoppo] renamed predictMembership() to predictSoft()
0f1d96e [Travis Galoppo] SPARK-5020 - Removed superfluous parameters from predictMembership()

1 files changed, 2 insertions, 7 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala
index 11a110db1f..b461ea4f0f 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala
@@ -45,7 +45,7 @@ class GaussianMixtureModel(
 
   /** Maps given points to their cluster indices. */
   def predict(points: RDD[Vector]): RDD[Int] = {
-    val responsibilityMatrix = predictMembership(points, mu, sigma, weight, k)
+    val responsibilityMatrix = predictSoft(points)
     responsibilityMatrix.map(r => r.indexOf(r.max))
   }
   
@@ -53,12 +53,7 @@ class GaussianMixtureModel(
    * Given the input vectors, return the membership value of each vector
    * to all mixture components. 
    */
-  def predictMembership(
-      points: RDD[Vector], 
-      mu: Array[Vector], 
-      sigma: Array[Matrix],
-      weight: Array[Double], 
-      k: Int): RDD[Array[Double]] = {
+  def predictSoft(points: RDD[Vector]): RDD[Array[Double]] = {
     val sc = points.sparkContext
     val dists = sc.broadcast {
       (0 until k).map { i =>