Packages

class RegressionTrainingNode extends TrainingNode[AnyVal, Double]

Created by maxhutch on 1/12/17.

Linear Supertypes
TrainingNode[AnyVal, Double], Serializable, AnyRef, Any
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Inherited
  1. RegressionTrainingNode
  2. TrainingNode
  3. Serializable
  4. AnyRef
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new RegressionTrainingNode(trainingData: Seq[(Vector[AnyVal], Double, Double)], leafLearner: Learner, splitter: Splitter[Double], split: Split, deltaImpurity: Double, numFeatures: Int, minLeafInstances: Int, remainingDepth: Int, maxDepth: Int)

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. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  8. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  9. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  10. def getFeatureImportance(): ArraySeq[Double]

    Get the feature importance from the subtree

    Get the feature importance from the subtree

    This routine sums the importance from the children and adds the local improvement to the feature used in this split

    returns

    feature importance as a vector

    Definition Classes
    RegressionTrainingNode → TrainingNode
  11. def getNode(): ModelNode[PredictionResult[Double]]

    Get the lightweight prediction node for the output tree

    Get the lightweight prediction node for the output tree

    returns

    lightweight prediction node

    Definition Classes
    RegressionTrainingNode → TrainingNode
  12. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  13. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  14. lazy val leftChild: TrainingNode[AnyVal, Double]
  15. lazy val leftTrain: Seq[(Vector[AnyVal], Double, Double)]
  16. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  17. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  18. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  19. lazy val rightChild: TrainingNode[AnyVal, Double]
  20. lazy val rightTrain: Seq[(Vector[AnyVal], Double, Double)]
  21. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  22. def toString(): String
    Definition Classes
    AnyRef → Any
  23. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  24. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
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    Annotations
    @throws(classOf[java.lang.InterruptedException])
  25. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
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    @throws(classOf[java.lang.InterruptedException]) @native()

Inherited from TrainingNode[AnyVal, Double]

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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