Packages

c

io.citrine.lolo.trees.classification

ClassificationResult

class ClassificationResult extends PredictionResult[Any]

Classification result

Linear Supertypes
PredictionResult[Any], AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. ClassificationResult
  2. PredictionResult
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new ClassificationResult(predictions: Seq[(PredictionResult[Char], TreeMeta)], outputEncoder: CategoricalEncoder[Any])

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[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  8. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  10. def getDepth(): Seq[Int]
  11. def getExpected(): Seq[Any]

    Get the expected values for this prediction

    Get the expected values for this prediction

    returns

    expected value of each prediction

    Definition Classes
    ClassificationResult → PredictionResult
  12. def getGradient(): Option[Seq[Vector[Double]]]

    Get the gradient or sensitivity of each prediction

    Get the gradient or sensitivity of each prediction

    returns

    a vector of doubles for each prediction

    Definition Classes
    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

    training row scores of each prediction

    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(): Option[Seq[Any]]

    Get the uncertainty of the prediction

    Get the uncertainty of the prediction

    For example, in regression this is sqrt(bias^2 + variance)

    returns

    uncertainty of each prediction

    Definition Classes
    PredictionResult
  16. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  17. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  18. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  19. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  20. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  21. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  22. def toString(): String
    Definition Classes
    AnyRef → Any
  23. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  24. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  25. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Inherited from PredictionResult[Any]

Inherited from AnyRef

Inherited from Any

Ungrouped