Class

ml.combust.mleap.core.regression

DecisionTreeRegressionModel

Related Doc: package regression

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case class DecisionTreeRegressionModel(rootNode: Node, numFeatures: Int) extends DecisionTree with Product with Serializable

Class for a decision tree regression model.

rootNode

root decision tree node

numFeatures

number of features used in prediction

Linear Supertypes
Product, Equals, DecisionTree, Serializable, Serializable, AnyRef, Any
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  1. DecisionTreeRegressionModel
  2. Product
  3. Equals
  4. DecisionTree
  5. Serializable
  6. Serializable
  7. AnyRef
  8. Any
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Instance Constructors

  1. new DecisionTreeRegressionModel(rootNode: Node, numFeatures: Int)

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    rootNode

    root decision tree node

    numFeatures

    number of features used in prediction

Value Members

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

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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

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    Definition Classes
    AnyRef → Any
  4. def apply(features: Vector): Double

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    Alias for ml.combust.mleap.core.regression.DecisionTreeRegressionModel#predict

    features

    features for prediction

    returns

    prediction

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  7. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  8. def finalize(): Unit

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

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

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

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

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

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    Definition Classes
    AnyRef
  14. val numFeatures: Int

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    number of features used in prediction

  15. def predict(features: Vector): Double

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    Predict value for given features.

    Predict value for given features.

    features

    features for predictoin

    returns

    prediction

  16. val rootNode: Node

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    root decision tree node

    root decision tree node

    Definition Classes
    DecisionTreeRegressionModelDecisionTree
  17. final def synchronized[T0](arg0: ⇒ T0): T0

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

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

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    Annotations
    @throws( ... )
  20. final def wait(arg0: Long): Unit

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    Definition Classes
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    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from DecisionTree

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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