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.  final def asInstanceOf[T0]: T0

   Definition Classes

   Any

5.  def clone(): AnyRef

   Attributes

   protected[lang]

   Definition Classes

   AnyRef

   Annotations

   @throws(classOf[java.lang.CloneNotSupportedException]) @native()

6.  final def eq(arg0: AnyRef): Boolean

   Definition Classes

   AnyRef

7.  lazy val expected: Seq[Any]
8.  lazy val expectedMatrix: Seq[Seq[Any]]
9.  def finalize(): Unit

   Attributes

   protected[lang]

   Definition Classes

   AnyRef

   Annotations

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

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

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

11.  def getExpected(): Seq[Any]

    Return the majority vote vote

    Return the majority vote vote

    returns

    expected value of each prediction

    Definition Classes

    BaggedClassificationResult → PredictionResult

12.  def getGradient(): Option[Seq[Vector[Double]]]

    Average the gradients from the models in the ensemble

    Average the gradients from the models in the ensemble

    returns

    the gradient of each prediction as a vector of doubles

    Definition Classes

    BaggedResult → PredictionResult

13.  def getImportanceScores(): Option[Seq[Seq[Double]]]

    Get the training row scores for each prediction

    Get the training row scores for each prediction

    returns

    sequence (over predictions) of sequence (over training rows) of importances

    Definition Classes

    PredictionResult

14.  def getInfluenceScores(actuals: Seq[Any]): Option[Seq[Seq[Double]]]

    Get the improvement (positive) or damage (negative) due to each training row on a prediction

    Get the improvement (positive) or damage (negative) due to each training row on a prediction

    actuals

    to assess the improvement or damage against

    returns

    Sequence (over predictions) of sequence (over training rows) of influence

    Definition Classes

    PredictionResult

15.  def getUncertainty(includeNoise: Boolean = true): Option[Seq[Any]]

    Get the "uncertainty" of the prediction

    Get the "uncertainty" of the prediction

    For regression, this should be the TotalError if non-observational and the StdDevObs if observational

    returns

    uncertainty of each prediction

    Definition Classes

    BaggedClassificationResult → PredictionResult

16.  final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

17.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

18.  final def notify(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

19.  final def notifyAll(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

20.  def numPredictions: Int

    The number of inputs that have been predicted on (NOT the number of bagged models).

    The number of inputs that have been predicted on (NOT the number of bagged models).

    Definition Classes

    BaggedClassificationResult → BaggedResult

21.  val predictionEnsemble: Seq[Seq[Any]]
22.  val predictions: Seq[PredictionResult[Any]]

    Definition Classes

    BaggedClassificationResult → BaggedResult

23.  def productElementNames: Iterator[String]

    Definition Classes

    Product

24.  final def synchronized[T0](arg0: => T0): T0

    Definition Classes

    AnyRef

25.  lazy val uncertainty: Seq[Map[Any, Double]]
26.  final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws(classOf[java.lang.InterruptedException])

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

    Definition Classes

    AnyRef

    Annotations

    @throws(classOf[java.lang.InterruptedException])

28.  final def wait(arg0: Long): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws(classOf[java.lang.InterruptedException]) @native()