Class/Object

ml.combust.mleap.core.regression

RandomForestRegressionModel

Related Docs: object RandomForestRegressionModel | package regression

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case class RandomForestRegressionModel(trees: Seq[DecisionTreeRegressionModel], treeWeights: Seq[Double], numFeatures: Int) extends TreeEnsemble with Serializable with Product

Class for random forest regression.

trees

trees in the random forest

numFeatures

number of features needed for prediction

Linear Supertypes
Product, Equals, Serializable, Serializable, TreeEnsemble, AnyRef, Any
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Inherited
  1. RandomForestRegressionModel
  2. Product
  3. Equals
  4. Serializable
  5. Serializable
  6. TreeEnsemble
  7. AnyRef
  8. Any
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Visibility
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Instance Constructors

  1. new RandomForestRegressionModel(trees: Seq[DecisionTreeRegressionModel], treeWeights: Seq[Double], numFeatures: Int)

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    trees

    trees in the random forest

    numFeatures

    number of features needed for 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.RandomForestRegressionModel#predict.

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

    features

    feature 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 needed for prediction

  15. def numTrees: Int

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    Number of trees in the ensemble

    Number of trees in the ensemble

    Definition Classes
    TreeEnsemble

  16. def predict(features: Vector): Double

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    Predict a value with the forest.

    Predict a value with the forest.

    features

    features for prediction

    returns

    prediction

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

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    Definition Classes
    AnyRef

  18. val treeWeights: Seq[Double]

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    Weights for each tree.

    Weights for each tree.

    Definition Classes
    RandomForestRegressionModel → TreeEnsemble

  19. val trees: Seq[DecisionTreeRegressionModel]

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    trees in the random forest

    trees in the random forest

    Definition Classes
    RandomForestRegressionModel → TreeEnsemble

  20. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from Serializable

Inherited from Serializable

Inherited from TreeEnsemble

Inherited from AnyRef

Inherited from Any

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