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 56b4bacdfc8c8..de032f6f58ac7 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
@@ -79,7 +79,7 @@ private[clustering] trait KMeansParams
     (value: String) => MLlibKMeans.validateInitializationMode(value))
 
   /** @group getParam */
-  def getInitializationMode: String = $(initMode)
+  def getInitMode: String = $(initMode)
 
   /**
    * Param for the number of steps for the k-means|| initialization mode. This is an advanced
@@ -164,7 +164,7 @@ class KMeans(override val uid: String) extends Estimator[KMeansModel] with KMean
   def setK(value: Int): this.type = set(k, value)
 
   /** @group setParam */
-  def setInitializationMode(value: String): this.type = set(initMode, value)
+  def setInitMode(value: String): this.type = set(initMode, value)
 
   /** @group setParam */
   def setInitializationSteps(value: Int): this.type = set(initSteps, value)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
index 7b7ae0dd8dfc1..374c00fe9b660 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
@@ -53,7 +53,7 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext {
     assert(kmeans.getPredictionCol === "prediction")
     assert(kmeans.getMaxIter === 20)
     assert(kmeans.getRuns === 1)
-    assert(kmeans.getInitializationMode === MLlibKMeans.K_MEANS_PARALLEL)
+    assert(kmeans.getInitMode === MLlibKMeans.K_MEANS_PARALLEL)
     assert(kmeans.getInitializationSteps === 5)
     assert(kmeans.getEpsilon === 1e-4)
   }
@@ -65,7 +65,7 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext {
       .setPredictionCol("test_prediction")
       .setMaxIter(33)
       .setRuns(7)
-      .setInitializationMode(MLlibKMeans.RANDOM)
+      .setInitMode(MLlibKMeans.RANDOM)
       .setInitializationSteps(3)
       .setSeed(123)
       .setEpsilon(1e-3)
@@ -75,7 +75,7 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext {
     assert(kmeans.getPredictionCol === "test_prediction")
     assert(kmeans.getMaxIter === 33)
     assert(kmeans.getRuns === 7)
-    assert(kmeans.getInitializationMode === MLlibKMeans.RANDOM)
+    assert(kmeans.getInitMode === MLlibKMeans.RANDOM)
     assert(kmeans.getInitializationSteps === 3)
     assert(kmeans.getSeed === 123)
     assert(kmeans.getEpsilon === 1e-3)
@@ -86,7 +86,7 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext {
       new KMeans().setK(1)
     }
     intercept[IllegalArgumentException] {
-      new KMeans().setInitializationMode("no_such_a_mode")
+      new KMeans().setInitMode("no_such_a_mode")
     }
     intercept[IllegalArgumentException] {
       new KMeans().setInitializationSteps(0)
diff --git a/python/pyspark/ml/clustering.py b/python/pyspark/ml/clustering.py
index 75837b58587b4..2a56c13e98f84 100644
--- a/python/pyspark/ml/clustering.py
+++ b/python/pyspark/ml/clustering.py
@@ -147,21 +147,21 @@ def getRuns(self):
         """
         return self.getOrDefault(self.runs)
 
-    def setInitializationMode(self, value):
+    def setInitMode(self, value):
         """
         Sets the value of :py:attr:`initMode`.
 
         >>> algo = KMeans()
-        >>> algo.getInitializationMode()
+        >>> algo.getInitMode()
         'k-means||'
-        >>> algo = algo.setInitializationMode("random")
-        >>> algo.getInitializationMode()
+        >>> algo = algo.setInitMode("random")
+        >>> algo.getInitMode()
         'random'
         """
         self._paramMap[self.initMode] = value
         return self
 
-    def getInitializationMode(self):
+    def getInitMode(self):
         """
         Gets the value of `initMode`
         """