Class/Object

ml.combust.mleap.core.regression

GBTRegressionModel

Related Docs: object GBTRegressionModel | package regression

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

Class for gradient boosted tree regression model.

trees

trees in model

treeWeights

weight of each tree

numFeatures

number of features

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

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

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    trees

    trees in model

    treeWeights

    weight of each tree

    numFeatures

    number of features

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.GBTRegressionModel#predict

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

    features

    features to predict

    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. def inputSchema: StructType

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    Definition Classes
    GBTRegressionModel → Model

  11. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  13. final def notify(): Unit

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    Definition Classes
    AnyRef

  14. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  15. val numFeatures: Int

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    number of features

  16. def numTrees: Int

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    Number of trees in the ensemble

    Number of trees in the ensemble

    Definition Classes
    TreeEnsemble

  17. def outputSchema: StructType

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    Definition Classes
    GBTRegressionModel → Model

  18. def predict(features: Vector): Double

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    Make prediction based on feature vector.

    Make prediction based on feature vector.

    features

    features to predict

    returns

    prediction

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

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    Definition Classes
    AnyRef

  20. val treeWeights: Seq[Double]

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    weight of each tree

    weight of each tree

    Definition Classes
    GBTRegressionModel → TreeEnsemble

  21. val trees: Seq[DecisionTreeRegressionModel]

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    trees in model

    trees in model

    Definition Classes
    GBTRegressionModel → TreeEnsemble

  22. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Model

Inherited from TreeEnsemble

Inherited from AnyRef

Inherited from Any

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