diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
index 0c56629e5fbc1..0b2dede657e6e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
@@ -36,14 +36,6 @@ import org.apache.spark.util.Utils
 private[clustering] trait KMeansParams
     extends Params with HasMaxIter with HasFeaturesCol with HasSeed with HasPredictionCol {
 
-  setDefault(k, 2)
-  setDefault(maxIter, 20)
-  setDefault(runs, 1)
-  setDefault(initializationMode, MLlibKMeans.K_MEANS_PARALLEL)
-  setDefault(initializationSteps, 5)
-  setDefault(epsilon, 1e-4)
-  setDefault(seed, Utils.random.nextLong())
-
   /**
    * Param for the column name for the number of clusters to create.
    * @group param
@@ -152,6 +144,14 @@ class KMeansModel private[ml] (
 @Experimental
 class KMeans(override val uid: String) extends Estimator[KMeansModel] with KMeansParams {
 
+  setDefault(k, 2)
+  setDefault(maxIter, 20)
+  setDefault(runs, 1)
+  setDefault(initializationMode, MLlibKMeans.K_MEANS_PARALLEL)
+  setDefault(initializationSteps, 5)
+  setDefault(epsilon, 1e-4)
+  setDefault(seed, Utils.random.nextLong())
+
   override def copy(extra: ParamMap): Estimator[KMeansModel] = defaultCopy(extra)
 
   def this() = this(Identifiable.randomUID("kmeans"))