diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
index e83ccfb075a00..5a60bed2652f7 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
@@ -68,16 +68,12 @@ private[clustering] trait BisectingKMeansParams extends Params with HasMaxIter
     "The minimum number of points (if >= 1.0) or the minimum proportion " +
       "of points (if < 1.0) of a divisible cluster.", ParamValidators.gt(0.0))
 
-
-  setDefault(
-    k -> 4,
-    maxIter -> 20,
-    minDivisibleClusterSize -> 1.0)
-
   /** @group expertGetParam */
   @Since("2.0.0")
   def getMinDivisibleClusterSize: Double = $(minDivisibleClusterSize)
 
+  setDefault(k -> 4, maxIter -> 20, minDivisibleClusterSize -> 1.0)
+
   /**
    * Validates and transforms the input schema.
    * @param schema input schema
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
index 45dbf1a16cb29..996036e2d6330 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
@@ -59,11 +59,7 @@ private[clustering] trait GaussianMixtureParams extends Params with HasMaxIter w
   @Since("2.0.0")
   def getK: Int = $(k)
 
-  setDefault(
-    k -> 2,
-    maxIter -> 100,
-    tol -> 0.01,
-    blockSize -> 1)
+  setDefault(k -> 2, maxIter -> 100, tol -> 0.01, blockSize -> 1)
 
   /**
    * Validates and transforms the input schema.
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 954c78f356936..5c06973e618bd 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
@@ -87,13 +87,8 @@ private[clustering] trait KMeansParams extends Params with HasMaxIter with HasFe
   @Since("1.5.0")
   def getInitSteps: Int = $(initSteps)
 
-  setDefault(
-    k -> 2,
-    maxIter -> 20,
-    initMode -> MLlibKMeans.K_MEANS_PARALLEL,
-    initSteps -> 2,
-    tol -> 1e-4,
-    distanceMeasure -> DistanceMeasure.EUCLIDEAN)
+  setDefault(k -> 2, maxIter -> 20, initMode -> MLlibKMeans.K_MEANS_PARALLEL, initSteps -> 2,
+    tol -> 1e-4, distanceMeasure -> DistanceMeasure.EUCLIDEAN)
 
   /**
    * Validates and transforms the input schema.
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
index 1b16e4d89292b..235a7f9b6ebd5 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
@@ -220,8 +220,6 @@ class LinearRegression @Since("1.3.0") (@Since("1.3.0") override val uid: String
   @Since("1.5.0")
   def setStandardization(value: Boolean): this.type = set(standardization, value)
 
-
-
   /**
    * Set the ElasticNet mixing parameter.
    * For alpha = 0, the penalty is an L2 penalty.
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index 3ee3df1f9638e..463dbee9a3b77 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -604,7 +604,6 @@ def __init__(self, featuresCol="features", labelCol="label", predictionCol="pred
         super(LinearSVC, self).__init__()
         self._java_obj = self._new_java_obj(
             "org.apache.spark.ml.classification.LinearSVC", self.uid)
-
         kwargs = self._input_kwargs
         self.setParams(**kwargs)