Packages

c

io.citrine.lolo.bags

BaggerHelper

case class BaggerHelper(models: ParSeq[Model[PredictionResult[Any]]], trainingData: Seq[(Vector[Any], Any)], Nib: Vector[Vector[Int]], useJackknife: Boolean, uncertaintyCalibration: Boolean) extends Product with Serializable

Helper class to subsume shared functionality of Bagger and MultiTaskBagger.

models

collection of trained models

trainingData

on which models were trained

Nib

vector (over models) of vectors (over training data) of the number of repeats in each model's bag

useJackknife

whether to use jackknife for uncertainty quantification

uncertaintyCalibration

whether to apply empirical uncertainty calibration

Attributes
protected
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Instance Constructors

  1. new BaggerHelper(models: ParSeq[Model[PredictionResult[Any]]], trainingData: Seq[(Vector[Any], Any)], Nib: Vector[Vector[Int]], useJackknife: Boolean, uncertaintyCalibration: Boolean)

    models

    collection of trained models

    trainingData

    on which models were trained

    Nib

    vector (over models) of vectors (over training data) of the number of repeats in each model's bag

    useJackknife

    whether to use jackknife for uncertainty quantification

    uncertaintyCalibration

    whether to apply empirical uncertainty calibration

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. val Nib: Vector[Vector[Int]]
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. lazy val biasTraining: Seq[(Vector[Any], Double)]

    Data on which to train a bias learner.

  7. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
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    @native() @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
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    @throws( classOf[java.lang.Throwable] )
  10. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  11. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  12. val isRegression: Boolean
  13. val models: ParSeq[Model[PredictionResult[Any]]]
  14. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  15. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  16. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  17. lazy val oobErrors: Seq[(Vector[Any], Double, Double)]

    Seq of tuples containing training data paired with their out-of-bag residuals and uncertainty estimates.

  18. val ratio: Double

    Calculate the uncertainty calibration ratio, which is the 68th percentile of error/uncertainty.

    Calculate the uncertainty calibration ratio, which is the 68th percentile of error/uncertainty. for the training points. If a point has 0 uncertainty, the ratio is 1 iff error is also 0, or infinity otherwise.

  19. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  20. val trainingData: Seq[(Vector[Any], Any)]
  21. val uncertaintyCalibration: Boolean
  22. val useJackknife: Boolean
  23. final def wait(): Unit
    Definition Classes
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    @throws( ... )
  24. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
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    @throws( ... )
  25. final def wait(arg0: Long): Unit
    Definition Classes
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    @native() @throws( ... )

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