org.apache.spark.mllib.tree.model

DecisionTreeModel

class DecisionTreeModel extends Serializable

:: Experimental :: Model to store the decision tree parameters

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@Experimental()
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Instance Constructors

  1. new DecisionTreeModel(topNode: Node, algo: Algo)

    topNode

    root node

    algo

    algorithm type -- classification or regression

Value Members

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

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  6. val algo: Algo

    algorithm type -- classification or regression

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  11. def finalize(): Unit

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

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. def predict(features: RDD[Vector]): RDD[Double]

    Predict values for the given data set using the model trained.

    Predict values for the given data set using the model trained.

    features

    RDD representing data points to be predicted

    returns

    RDD[Int] where each entry contains the corresponding prediction

  19. 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

    Double prediction from the trained model

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

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  21. def toString(): String

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  22. val topNode: Node

    root node

  23. final def wait(): Unit

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

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

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