GradientBoostedTreesModel

Value Members

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

   

   Definition Classes

   AnyRef → Any

2. final def ##(): Int

   

   Definition Classes

   AnyRef → Any

3. final def ==(arg0: Any): Boolean

   

   Definition Classes

   AnyRef → Any

4. 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

   Annotations

   @Since( "1.2.0" )

5. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

6. def clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

7. val combiningStrategy: EnsembleCombiningStrategy

   

   Attributes

   protected

   Definition Classes

   TreeEnsembleModel

8. final def eq(arg0: AnyRef): Boolean

   

   Definition Classes

   AnyRef

9. def equals(arg0: Any): Boolean

   

   Definition Classes

   AnyRef → Any

10. def evaluateEachIteration(data: RDD[LabeledPoint], loss: Loss): Array[Double]

    

    Method to compute error or loss for every iteration of gradient boosting.

    Method to compute error or loss for every iteration of gradient boosting.

    data

    RDD of org.apache.spark.mllib.regression.LabeledPoint

    loss

    evaluation metric.

    returns

    an array with index i having the losses or errors for the ensemble containing the first i+1 trees

    Annotations

    @Since( "1.4.0" )

11. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

12. def formatVersion: String

    

    Current version of model save/load format.

    Current version of model save/load format.

    Attributes

    protected

    Definition Classes

    GradientBoostedTreesModel → Saveable

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 ensemble.

    Get number of trees in ensemble.

    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. def save(sc: SparkContext, path: String): Unit

    
    sc

    Spark context used to save model data.

    path

    Path specifying the directory in which to save this model. If the directory already exists, this method throws an exception.

    Definition Classes

    GradientBoostedTreesModel → Saveable

    Annotations

    @Since( "1.3.0" )

24. final def synchronized[T0](arg0: ⇒ T0): T0

    

    Definition Classes

    AnyRef

25. def toDebugString: String

    

    Print the full model to a string.

    Print the full model to a string.

    Definition Classes

    TreeEnsembleModel

26. def toString(): String

    

    Print a summary of the model.

    Print a summary of the model.

    Definition Classes

    TreeEnsembleModel → AnyRef → Any

27. def totalNumNodes: Int

    

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

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

    Definition Classes

    TreeEnsembleModel

28. val treeWeights: Array[Double]

    

    tree ensemble weights

    tree ensemble weights

    Definition Classes

    GradientBoostedTreesModel → TreeEnsembleModel

    Annotations

    @Since( "1.2.0" )

29. val trees: Array[DecisionTreeModel]

    

    tree ensembles

    tree ensembles

    Definition Classes

    GradientBoostedTreesModel → TreeEnsembleModel

    Annotations

    @Since( "1.2.0" )

30. final def wait(): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

31. final def wait(arg0: Long, arg1: Int): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

32. final def wait(arg0: Long): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )