diff options
8 files changed, 16 insertions, 16 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala index 1943a4a747..ecb218e2a3 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala @@ -44,7 +44,7 @@ import org.apache.spark.sql.Dataset */ @Since("1.4.0") @Experimental -final class DecisionTreeClassifier @Since("1.4.0") ( +class DecisionTreeClassifier @Since("1.4.0") ( @Since("1.4.0") override val uid: String) extends ProbabilisticClassifier[Vector, DecisionTreeClassifier, DecisionTreeClassificationModel] with DecisionTreeClassifierParams with DefaultParamsWritable { @@ -138,7 +138,7 @@ object DecisionTreeClassifier extends DefaultParamsReadable[DecisionTreeClassifi */ @Since("1.4.0") @Experimental -final class DecisionTreeClassificationModel private[ml] ( +class DecisionTreeClassificationModel private[ml] ( @Since("1.4.0")override val uid: String, @Since("1.4.0")override val rootNode: Node, @Since("1.6.0")override val numFeatures: Int, diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala index 1bd6dae7dd..e736f01cc6 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala @@ -57,7 +57,7 @@ import org.apache.spark.sql.functions._ */ @Since("1.4.0") @Experimental -final class GBTClassifier @Since("1.4.0") ( +class GBTClassifier @Since("1.4.0") ( @Since("1.4.0") override val uid: String) extends Predictor[Vector, GBTClassifier, GBTClassificationModel] with GBTClassifierParams with DefaultParamsWritable with Logging { @@ -170,7 +170,7 @@ object GBTClassifier extends DefaultParamsReadable[GBTClassifier] { */ @Since("1.6.0") @Experimental -final class GBTClassificationModel private[ml]( +class GBTClassificationModel private[ml]( @Since("1.6.0") override val uid: String, private val _trees: Array[DecisionTreeRegressionModel], private val _treeWeights: Array[Double], diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala index c04ecc88ae..28364c2593 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala @@ -44,7 +44,7 @@ import org.apache.spark.sql.functions._ */ @Since("1.4.0") @Experimental -final class RandomForestClassifier @Since("1.4.0") ( +class RandomForestClassifier @Since("1.4.0") ( @Since("1.4.0") override val uid: String) extends ProbabilisticClassifier[Vector, RandomForestClassifier, RandomForestClassificationModel] with RandomForestClassifierParams with DefaultParamsWritable { @@ -149,7 +149,7 @@ object RandomForestClassifier extends DefaultParamsReadable[RandomForestClassifi */ @Since("1.4.0") @Experimental -final class RandomForestClassificationModel private[ml] ( +class RandomForestClassificationModel private[ml] ( @Since("1.5.0") override val uid: String, private val _trees: Array[DecisionTreeClassificationModel], @Since("1.6.0") override val numFeatures: Int, diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala index c04c416aaf..339a8cf486 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala @@ -45,7 +45,7 @@ import org.apache.spark.sql.functions._ */ @Since("1.4.0") @Experimental -final class DecisionTreeRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String) +class DecisionTreeRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String) extends Predictor[Vector, DecisionTreeRegressor, DecisionTreeRegressionModel] with DecisionTreeRegressorParams with DefaultParamsWritable { @@ -129,7 +129,7 @@ object DecisionTreeRegressor extends DefaultParamsReadable[DecisionTreeRegressor */ @Since("1.4.0") @Experimental -final class DecisionTreeRegressionModel private[ml] ( +class DecisionTreeRegressionModel private[ml] ( override val uid: String, override val rootNode: Node, override val numFeatures: Int) diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala index da51cb7800..c41fb4b062 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala @@ -57,7 +57,7 @@ import org.apache.spark.sql.functions._ */ @Since("1.4.0") @Experimental -final class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String) +class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String) extends Predictor[Vector, GBTRegressor, GBTRegressionModel] with GBTRegressorParams with DefaultParamsWritable with Logging { @@ -157,7 +157,7 @@ object GBTRegressor extends DefaultParamsReadable[GBTRegressor] { */ @Since("1.4.0") @Experimental -final class GBTRegressionModel private[ml]( +class GBTRegressionModel private[ml]( override val uid: String, private val _trees: Array[DecisionTreeRegressionModel], private val _treeWeights: Array[Double], diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala index 8eaed8b682..b6ab2fd625 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala @@ -43,7 +43,7 @@ import org.apache.spark.sql.functions._ */ @Since("1.4.0") @Experimental -final class RandomForestRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String) +class RandomForestRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String) extends Predictor[Vector, RandomForestRegressor, RandomForestRegressionModel] with RandomForestRegressorParams with DefaultParamsWritable { @@ -137,7 +137,7 @@ object RandomForestRegressor extends DefaultParamsReadable[RandomForestRegressor */ @Since("1.4.0") @Experimental -final class RandomForestRegressionModel private[ml] ( +class RandomForestRegressionModel private[ml] ( override val uid: String, private val _trees: Array[DecisionTreeRegressionModel], override val numFeatures: Int) diff --git a/mllib/src/main/scala/org/apache/spark/ml/tree/Node.scala b/mllib/src/main/scala/org/apache/spark/ml/tree/Node.scala index b5cb378829..f71d28cf59 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/tree/Node.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/tree/Node.scala @@ -115,7 +115,7 @@ private[ml] object Node { * @param impurity Impurity measure at this node (for training data) */ @DeveloperApi -final class LeafNode private[ml] ( +class LeafNode private[ml] ( override val prediction: Double, override val impurity: Double, override private[ml] val impurityStats: ImpurityCalculator) extends Node { @@ -158,7 +158,7 @@ final class LeafNode private[ml] ( * @param split Information about the test used to split to the left or right child. */ @DeveloperApi -final class InternalNode private[ml] ( +class InternalNode private[ml] ( override val prediction: Double, override val impurity: Double, val gain: Double, diff --git a/mllib/src/main/scala/org/apache/spark/ml/tree/Split.scala b/mllib/src/main/scala/org/apache/spark/ml/tree/Split.scala index 5d11ed0971..a4287483d1 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/tree/Split.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/tree/Split.scala @@ -75,7 +75,7 @@ private[tree] object Split { * @param numCategories Number of categories for this feature. */ @DeveloperApi -final class CategoricalSplit private[ml] ( +class CategoricalSplit private[ml] ( override val featureIndex: Int, _leftCategories: Array[Double], @Since("2.0.0") val numCategories: Int) @@ -160,7 +160,7 @@ final class CategoricalSplit private[ml] ( * Otherwise, it goes right. */ @DeveloperApi -final class ContinuousSplit private[ml] (override val featureIndex: Int, val threshold: Double) +class ContinuousSplit private[ml] (override val featureIndex: Int, val threshold: Double) extends Split { override private[ml] def shouldGoLeft(features: Vector): Boolean = { |