diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
index f98b0b536d..b9621530ef 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
@@ -119,7 +119,7 @@ abstract class GeneralizedLinearAlgorithm[M <: GeneralizedLinearModel]
    */
   def run(input: RDD[LabeledPoint]) : M = {
     val nfeatures: Int = input.first().features.length
-    val initialWeights = Array.fill(nfeatures)(1.0)
+    val initialWeights = new Array[Double](nfeatures)
     run(input, initialWeights)
   }
 
@@ -134,15 +134,15 @@ abstract class GeneralizedLinearAlgorithm[M <: GeneralizedLinearModel]
       throw new SparkException("Input validation failed.")
     }
 
-    // Add a extra variable consisting of all 1.0's for the intercept.
+    // Prepend an extra variable consisting of all 1.0's for the intercept.
     val data = if (addIntercept) {
-      input.map(labeledPoint => (labeledPoint.label, Array(1.0, labeledPoint.features:_*)))
+      input.map(labeledPoint => (labeledPoint.label, labeledPoint.features.+:(1.0)))
     } else {
       input.map(labeledPoint => (labeledPoint.label, labeledPoint.features))
     }
 
     val initialWeightsWithIntercept = if (addIntercept) {
-      Array(1.0, initialWeights:_*)
+      initialWeights.+:(1.0)
     } else {
       initialWeights
     }