Class

regressors

RandomRegressor

Related Doc: package regressors

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class RandomRegressor extends Regressor

Random regressor

This is a regressor providing random predictions

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Regressor, AnyRef, Any
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Instance Constructors

  1. new RandomRegressor()

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Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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    Any

  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    AnyRef
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    @throws( ... )

  6. def diagnostics(): Map[String, List[(Double, Double)]]

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    Provides meta-information on the regressor

    Provides meta-information on the regressor

    returns

    Map object of metric names and metric values

    Definition Classes
    Regressor

  7. final def eq(arg0: AnyRef): Boolean

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    AnyRef

  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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    protected[java.lang]
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    AnyRef
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    @throws( classOf[java.lang.Throwable] )

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

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    AnyRef → Any

  11. def hashCode(): Int

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    AnyRef → Any

  12. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  13. val name: String

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    The name of the regressor

    The name of the regressor

    Definition Classes
    RandomRegressor → Regressor

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

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    Definition Classes
    AnyRef

  15. final def notify(): Unit

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    Definition Classes
    AnyRef

  16. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  17. def predict(X: List[List[Double]]): List[Double]

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    Applies the trained regressor to a dataset

    Applies the trained regressor to a dataset

    X

    List of data instances

    returns

    List of predictions

    Definition Classes
    RandomRegressor → Regressor

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

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    Definition Classes
    AnyRef

  19. def toString(): String

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  20. def train(X: List[List[Double]], y: List[Double]): Unit

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    Performs the training of the regressor

    Performs the training of the regressor

    X

    List of training instances

    y

    List of training labels

    Definition Classes
    RandomRegressor → Regressor

  21. final def wait(): Unit

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    @throws( ... )

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

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

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Inherited from Regressor

Inherited from AnyRef

Inherited from Any

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