address comments

apache · Jul 16, 2020 · 4bc1053 · 4bc1053
1 parent 72c17e9
commit 4bc1053
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Showing 5 changed files with 5 additions and 21 deletions.
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
@@ -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
@@ -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
@@ -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
@@ -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
@@ -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)