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 2166c6bb6b443..3e1ed91bf6729 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
@@ -44,7 +44,7 @@ abstract class GeneralizedLinearModel(val weights: Array[Double], val intercept:
    * @param weightMatrix Column vector containing the weights of the model
    * @param intercept Intercept of the model.
    */
-  protected def predictPoint(dataMatrix: DoubleMatrix, weightMatrix: DoubleMatrix,
+  def predictPoint(dataMatrix: DoubleMatrix, weightMatrix: DoubleMatrix,
     intercept: Double): Double
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala
index e397a573079e5..be63ce8538fef 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala
@@ -36,7 +36,7 @@ class LassoModel(
   extends GeneralizedLinearModel(weights, intercept)
   with RegressionModel with Serializable {
 
-  override protected def predictPoint(
+  override def predictPoint(
       dataMatrix: DoubleMatrix,
       weightMatrix: DoubleMatrix,
       intercept: Double): Double = {
@@ -85,7 +85,7 @@ class LassoWithSGD private (
     this
   }
 
-  override protected def createModel(weights: Array[Double], intercept: Double) = {
+  override def createModel(weights: Array[Double], intercept: Double) = {
     val weightsMat = new DoubleMatrix(weights.length, 1, weights: _*)
     val weightsScaled = weightsMat.div(xColSd)
     val interceptScaled = yMean - weightsMat.transpose().mmul(xColMean.div(xColSd)).get(0)
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala
index b4aafbe8bcaff..f5f15d1a33f4d 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala
@@ -35,7 +35,7 @@ class LinearRegressionModel(
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept) with RegressionModel with Serializable {
 
-  override protected def predictPoint(
+  override def predictPoint(
       dataMatrix: DoubleMatrix,
       weightMatrix: DoubleMatrix,
       intercept: Double): Double = {
@@ -69,7 +69,7 @@ class LinearRegressionWithSGD private (
    */
   def this() = this(1.0, 100, 1.0)
 
-  override protected def createModel(weights: Array[Double], intercept: Double) = {
+  override def createModel(weights: Array[Double], intercept: Double) = {
     new LinearRegressionModel(weights, intercept)
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala
index 325e78c8f2233..feb100f21888f 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala
@@ -36,7 +36,7 @@ class RidgeRegressionModel(
   extends GeneralizedLinearModel(weights, intercept)
   with RegressionModel with Serializable {
 
-  override protected def predictPoint(
+  override def predictPoint(
       dataMatrix: DoubleMatrix,
       weightMatrix: DoubleMatrix,
       intercept: Double): Double = {
@@ -86,7 +86,7 @@ class RidgeRegressionWithSGD private (
     this
   }
 
-  override protected def createModel(weights: Array[Double], intercept: Double) = {
+  override def createModel(weights: Array[Double], intercept: Double) = {
     val weightsMat = new DoubleMatrix(weights.length, 1, weights: _*)
     val weightsScaled = weightsMat.div(xColSd)
     val interceptScaled = yMean - weightsMat.transpose().mmul(xColMean.div(xColSd)).get(0)