fix formatting and use Vector instead of List to maintain order

mllib/src/main/scala/spark/mllib/regression/RidgeRegression.scala

@@ -15,7 +15,7 @@ class RidgeRegressionModel(
     val weights: DoubleMatrix,
     val intercept: Double,
     val lambdaOpt: Double,
-    val lambdas: List[(Double, Double, DoubleMatrix)])
+    val lambdas: Seq[(Double, Double, DoubleMatrix)])
   extends RegressionModel {
 
   override def predict(testData: RDD[Array[Double]]): RDD[Double] = {
@@ -99,12 +99,10 @@ class RidgeRegression private (var lambdaLow: Double, var lambdaHigh: Double)
     }
 
     // Binary search for the best assignment to lambda.
-    def binSearch(low: Double, high: Double): List[(Double, Double, DoubleMatrix)] = {
+    def binSearch(low: Double, high: Double): Seq[(Double, Double, DoubleMatrix)] = {
       @tailrec
-      def loop(
-        low: Double,
-        high: Double,
-        acc: List[(Double, Double, DoubleMatrix)]): List[(Double, Double, DoubleMatrix)] = {
+      def loop(low: Double, high: Double, acc: Seq[(Double, Double, DoubleMatrix)])
+        : Seq[(Double, Double, DoubleMatrix)] = {
         val mid = (high - low) / 2 + low
         val lowValue = crossValidate((mid - low) / 2 + low)
         val highValue = crossValidate((high - mid) / 2 + mid)
@@ -114,14 +112,13 @@ class RidgeRegression private (var lambdaLow: Double, var lambdaHigh: Double)
           (mid - (high-low)/4, high)
         }
         if (newHigh - newLow > 1.0E-7) {
-          // :: is list prepend in Scala.
-          loop(newLow, newHigh, lowValue :: highValue :: acc)
+          loop(newLow, newHigh, acc :+ lowValue :+ highValue)
         } else {
-          lowValue :: highValue :: acc
+          acc :+ lowValue :+ highValue
         }
       }
 
-      loop(low, high, Nil)
+      loop(low, high, Vector.empty)
     }
 
     // Actually compute the best lambda
@@ -143,6 +140,7 @@ class RidgeRegression private (var lambdaLow: Double, var lambdaHigh: Double)
     model
   }
 }
+
 /**
  * Top-level methods for calling Ridge Regression.
  */