@@ -214,7 +214,7 @@ object DecisionTree extends Serializable with Logging {
214214 */
215215 def train (input : RDD [LabeledPoint ], strategy : Strategy ): DecisionTreeModel = {
216216 // Converting from standard instance format to weighted input format for tree training
217- val weightedInput = input.map(x => WeightedLabeledPoint (x.label,x.features))
217+ val weightedInput = input.map(x => WeightedLabeledPoint (x.label, x.features))
218218 new DecisionTree (strategy).train(weightedInput : RDD [WeightedLabeledPoint ])
219219 }
220220
@@ -238,7 +238,7 @@ object DecisionTree extends Serializable with Logging {
238238 maxDepth : Int ): DecisionTreeModel = {
239239 val strategy = new Strategy (algo,impurity,maxDepth)
240240 // Converting from standard instance format to weighted input format for tree training
241- val weightedInput = input.map(x => WeightedLabeledPoint (x.label,x.features))
241+ val weightedInput = input.map(x => WeightedLabeledPoint (x.label, x.features))
242242 new DecisionTree (strategy).train(weightedInput : RDD [WeightedLabeledPoint ])
243243 }
244244
@@ -278,7 +278,7 @@ object DecisionTree extends Serializable with Logging {
278278 val strategy = new Strategy (algo, impurity, maxDepth, maxBins, quantileCalculationStrategy,
279279 categoricalFeaturesInfo)
280280 // Converting from standard instance format to weighted input format for tree training
281- val weightedInput = input.map(x => WeightedLabeledPoint (x.label,x.features))
281+ val weightedInput = input.map(x => WeightedLabeledPoint (x.label, x.features))
282282 new DecisionTree (strategy).train(weightedInput : RDD [WeightedLabeledPoint ])
283283 }
284284
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