diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala
index de3555a5b74d0..f8b56293e3ccc 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala
@@ -19,7 +19,7 @@ package org.apache.spark.ml.feature
 
 import org.apache.spark.annotation.AlphaComponent
 import org.apache.spark.ml.UnaryTransformer
-import org.apache.spark.ml.param.{Param, ParamMap}
+import org.apache.spark.ml.param.Param
 import org.apache.spark.mllib.feature
 import org.apache.spark.mllib.linalg.{Vector, VectorUDT}
 import org.apache.spark.sql.types.DataType
@@ -45,9 +45,9 @@ class ElementwiseProduct extends UnaryTransformer[Vector, Vector, ElementwisePro
   /** @group getParam */
   def getScalingVec: Vector = getOrDefault(scalingVec)
 
-  override protected def createTransformFunc(paramMap: ParamMap): Vector => Vector = {
-    require(paramMap.contains(scalingVec), s"transformation requires a weight vector: $scalingVec")
-    val elemScaler = new feature.ElementwiseProduct(paramMap(scalingVec))
+  override protected def createTransformFunc: Vector => Vector = {
+    require(params.contains(scalingVec), s"transformation requires a weight vector")
+    val elemScaler = new feature.ElementwiseProduct($(scalingVec))
     elemScaler.transform
   }