org.apache.spark.mllib.tree.model

GradientBoostedTreesModel

class GradientBoostedTreesModel extends TreeEnsembleModel

:: Experimental :: Represents a gradient boosted trees model.

Annotations
@Experimental()
Linear Supertypes
TreeEnsembleModel, Serializable, Serializable, AnyRef, Any
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  1. GradientBoostedTreesModel
  2. TreeEnsembleModel
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  4. Serializable
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Instance Constructors

  1. new GradientBoostedTreesModel(algo: Algo, trees: Array[DecisionTreeModel], treeWeights: Array[Double])

    algo

    algorithm for the ensemble model, either Classification or Regression

    trees

    tree ensembles

    treeWeights

    tree ensemble weights

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. val algo: Algo

    algorithm for the ensemble model, either Classification or Regression

    algorithm for the ensemble model, either Classification or Regression

    Definition Classes
    GradientBoostedTreesModel → TreeEnsembleModel
  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  8. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. val combiningStrategy: EnsembleCombiningStrategy

    Attributes
    protected
    Definition Classes
    TreeEnsembleModel
  10. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  11. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  12. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  13. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  14. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  16. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  17. final def notify(): Unit

    Definition Classes
    AnyRef
  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  19. def numTrees: Int

    Get number of trees in forest.

    Get number of trees in forest.

    Definition Classes
    TreeEnsembleModel
  20. def predict(features: JavaRDD[Vector]): JavaRDD[Double]

    Java-friendly version of org.apache.spark.mllib.tree.model.TreeEnsembleModel#predict.

    Java-friendly version of org.apache.spark.mllib.tree.model.TreeEnsembleModel#predict.

    Definition Classes
    TreeEnsembleModel
  21. def predict(features: RDD[Vector]): RDD[Double]

    Predict values for the given data set.

    Predict values for the given data set.

    features

    RDD representing data points to be predicted

    returns

    RDD[Double] where each entry contains the corresponding prediction

    Definition Classes
    TreeEnsembleModel
  22. def predict(features: Vector): Double

    Predict values for a single data point using the model trained.

    Predict values for a single data point using the model trained.

    features

    array representing a single data point

    returns

    predicted category from the trained model

    Definition Classes
    TreeEnsembleModel
  23. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  24. def toDebugString: String

    Print the full model to a string.

    Print the full model to a string.

    Definition Classes
    TreeEnsembleModel
  25. def toString(): String

    Print a summary of the model.

    Print a summary of the model.

    Definition Classes
    TreeEnsembleModel → AnyRef → Any
  26. def totalNumNodes: Int

    Get total number of nodes, summed over all trees in the forest.

    Get total number of nodes, summed over all trees in the forest.

    Definition Classes
    TreeEnsembleModel
  27. val treeWeights: Array[Double]

    tree ensemble weights

    tree ensemble weights

    Definition Classes
    GradientBoostedTreesModel → TreeEnsembleModel
  28. val trees: Array[DecisionTreeModel]

    tree ensembles

    tree ensembles

    Definition Classes
    GradientBoostedTreesModel → TreeEnsembleModel
  29. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  30. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  31. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from TreeEnsembleModel

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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