diff --git a/mllib/src/main/scala/spark/mllib/optimization/Updater.scala b/mllib/src/main/scala/spark/mllib/optimization/Updater.scala
index bbf21e5c28459297ad34fe9780a131a2bf39c364..e916a92c332088638c02966ab6ffdf07ca417217 100644
--- a/mllib/src/main/scala/spark/mllib/optimization/Updater.scala
+++ b/mllib/src/main/scala/spark/mllib/optimization/Updater.scala
@@ -23,6 +23,7 @@ import org.jblas.DoubleMatrix
 abstract class Updater extends Serializable {
   /**
    * Compute an updated value for weights given the gradient, stepSize and iteration number.
+   * Also returns the regularization value computed using the *updated* weights.
    *
    * @param weightsOlds - Column matrix of size nx1 where n is the number of features.
    * @param gradient - Column matrix of size nx1 where n is the number of features.
@@ -31,7 +32,7 @@ abstract class Updater extends Serializable {
    * @param regParam - Regularization parameter
    *
    * @return A tuple of 2 elements. The first element is a column matrix containing updated weights,
-   *         and the second element is the regularization value.
+   *         and the second element is the regularization value computed using updated weights.
    */
   def compute(weightsOld: DoubleMatrix, gradient: DoubleMatrix, stepSize: Double, iter: Int, regParam: Double):
       (DoubleMatrix, Double)
@@ -46,13 +47,13 @@ class SimpleUpdater extends Updater {
 }
 
 /**
-* L1 regularization -- corresponding proximal operator is the soft-thresholding function
-* That is, each weight component is shrunk towards 0 by shrinkageVal
-* If w >  shrinkageVal, set weight component to w-shrinkageVal.
-* If w < -shrinkageVal, set weight component to w+shrinkageVal.
-* If -shrinkageVal < w < shrinkageVal, set weight component to 0.
-* Equivalently, set weight component to signum(w) * max(0.0, abs(w) - shrinkageVal)
-**/
+ * L1 regularization -- corresponding proximal operator is the soft-thresholding function
+ * That is, each weight component is shrunk towards 0 by shrinkageVal
+ * If w >  shrinkageVal, set weight component to w-shrinkageVal.
+ * If w < -shrinkageVal, set weight component to w+shrinkageVal.
+ * If -shrinkageVal < w < shrinkageVal, set weight component to 0.
+ * Equivalently, set weight component to signum(w) * max(0.0, abs(w) - shrinkageVal)
+ */
 class L1Updater extends Updater {
   override def compute(weightsOld: DoubleMatrix, gradient: DoubleMatrix,
       stepSize: Double, iter: Int, regParam: Double): (DoubleMatrix, Double) = {