fixing formatting

msjgriffiths · Oct 20, 2014 · 6a11c02 · 6a11c02
1 parent 823691b
commit 6a11c02
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Showing 3 changed files with 10 additions and 16 deletions.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoosting.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoosting.scala
@@ -48,7 +48,6 @@ class GradientBoosting (
    * @return GradientBoostingModel that can be used for prediction
    */
   def train(input: RDD[LabeledPoint]): GradientBoostingModel = {
-    val strategy = boostingStrategy.strategy
     val algo = boostingStrategy.algo
     algo match {
       case Regression => GradientBoosting.boost(input, boostingStrategy)
@@ -177,6 +176,7 @@ object GradientBoosting extends Logging {
       numClassesForClassification, categoricalFeaturesInfo = categoricalFeaturesInfo)
     new GradientBoosting(boostingStrategy).train(input)
   }
+
   /**
    * Java-friendly API for [[org.apache.spark.mllib.tree.GradientBoosting#trainRegressor]]
    *
@@ -223,7 +223,6 @@ object GradientBoosting extends Logging {
     new GradientBoosting(boostingStrategy).train(input)
   }
 
-
   /**
    * Java-friendly API for [[org.apache.spark.mllib.tree.GradientBoosting#trainClassifier]]
    *
@@ -274,7 +273,6 @@ object GradientBoosting extends Logging {
     new GradientBoosting(boostingStrategy).train(input)
   }
 
-
   /**
    * Method to train a gradient boosting regression model.
    *
@@ -310,7 +308,6 @@ object GradientBoosting extends Logging {
     new GradientBoosting(boostingStrategy).train(input)
   }
 
-
   /**
    * Method to train a gradient boosting binary classification model.
    *
@@ -346,7 +343,6 @@ object GradientBoosting extends Logging {
     new GradientBoosting(boostingStrategy).train(input)
   }
 
-
   /**
    * Method to train a gradient boosting regression model.
    *
@@ -373,16 +369,14 @@ object GradientBoosting extends Logging {
    * @param boostingStrategy Configuration options for the boosting algorithm.
    * @return GradientBoostingModel that can be used for prediction
    */
-  def trainClassification(
+  def trainClassifier(
       input: RDD[LabeledPoint],
       boostingStrategy: BoostingStrategy): GradientBoostingModel = {
     val algo = boostingStrategy.algo
     require(algo == Classification, s"Only Classification algo supported. Provided algo is $algo.")
     new GradientBoosting(boostingStrategy).train(input)
   }
 
-
-
   /**
    * Internal method for performing regression using trees as base learners.
    * @param input training dataset

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/impl/BaggedPoint.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/impl/BaggedPoint.scala
@@ -55,7 +55,7 @@ private[tree] object BaggedPoint {
    * @param withReplacement Sampling with/without replacement.
    * @return  BaggedPoint dataset representation
    */
-  def convertToBaggedRDD[Datum](
+  def convertToBaggedRDD[Datum] (
       input: RDD[Datum],
       subsample: Double,
       numSubsamples: Int,
@@ -71,7 +71,7 @@ private[tree] object BaggedPoint {
     }
   }
 
-  private[tree] def convertToBaggedRDDSamplingWithoutReplacement[Datum](
+  private[tree] def convertToBaggedRDDSamplingWithoutReplacement[Datum] (
       input: RDD[Datum],
       subsample: Double,
       numSubsamples: Int): RDD[BaggedPoint[Datum]] = {
@@ -95,7 +95,7 @@ private[tree] object BaggedPoint {
     }
   }
 
-  private[tree] def convertToBaggedRDDSamplingWithReplacement[Datum](
+  private[tree] def convertToBaggedRDDSamplingWithReplacement[Datum] (
       input: RDD[Datum],
       subsample: Double,
       numSubsamples: Int): RDD[BaggedPoint[Datum]] = {
@@ -115,8 +115,8 @@ private[tree] object BaggedPoint {
     }
   }
 
-  private[tree] def convertToBaggedRDDWithoutSampling[Datum]
-      (input: RDD[Datum]): RDD[BaggedPoint[Datum]] = {
+  private[tree] def convertToBaggedRDDWithoutSampling[Datum] (
+      input: RDD[Datum]): RDD[BaggedPoint[Datum]] = {
     input.map(datum => new BaggedPoint(datum, Array(1.0)))
   }
 

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/LogLoss.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/LogLoss.scala
@@ -36,9 +36,9 @@ object LogLoss extends Loss {
    */
   @DeveloperApi
   override def lossGradient(
-                             model: DecisionTreeModel,
-                             point: LabeledPoint,
-                             learningRate: Double): Double = {
+      model: DecisionTreeModel,
+      point: LabeledPoint,
+      learningRate: Double): Double = {
     val prediction = model.predict(point.features)
     val logLoss = 1.0 / (1.0 + math.exp(-prediction))
     point.label - logLoss * learningRate