GradientBoostedTreesModel

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 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

13. def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

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

14. def formatVersion: String

    Current version of model save/load format.

    Current version of model save/load format.

    Attributes

    protected

    Definition Classes

    GradientBoostedTreesModel → Saveable

15. final def getClass(): Class[_]

    Definition Classes

    AnyRef → Any

16. def hashCode(): Int

    Definition Classes

    AnyRef → Any

17. final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

18. final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

19. final def notify(): Unit

    Definition Classes

    AnyRef

20. final def notifyAll(): Unit

    Definition Classes

    AnyRef

21. def numTrees: Int

    Get number of trees in ensemble.

    Get number of trees in ensemble.

    Definition Classes

    TreeEnsembleModel

22. 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

23. 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

24. 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

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

    Save this model to the given path.

    Save this model to the given path.

    This saves:

    • human-readable (JSON) model metadata to path/metadata/
    • Parquet formatted data to path/data/

    The model may be loaded using Loader.load.

    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

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

    Definition Classes

    AnyRef

27. def toDebugString: String

    Print the full model to a string.

    Print the full model to a string.

    Definition Classes

    TreeEnsembleModel

28. def toString(): String

    Print a summary of the model.

    Print a summary of the model.

    Definition Classes

    TreeEnsembleModel → AnyRef → Any

29. 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

30. val treeWeights: Array[Double]

    tree ensemble weights

    tree ensemble weights

    Definition Classes

    GradientBoostedTreesModel → TreeEnsembleModel

31. val trees: Array[DecisionTreeModel]

    tree ensembles

    tree ensembles

    Definition Classes

    GradientBoostedTreesModel → TreeEnsembleModel

32. final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )