com.alpine.result

ClassificationResult

case class ClassificationResult(labels: Seq[String], confidences: Array[Double]) extends CategoricalResult with Product with Serializable

The value is the arg max of the confidences.

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Serializable, Serializable, Product, Equals, CategoricalResult, MLResult, AnyRef, Any
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  1. ClassificationResult
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. CategoricalResult
  7. MLResult
  8. AnyRef
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Instance Constructors

  1. new ClassificationResult(labels: Seq[String], confidences: Array[Double])

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def clone(): AnyRef

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

  8. val confidences: Array[Double]

  9. def details: Array[Double]

    A numeric detail generated by the model for each label.

    A numeric detail generated by the model for each label. Typically, this is a value which is minimized or maximized to determine the predicted value. e.g. confidence probabilities (to be maximised) or distance to the labelled cluster (to be minimised).

    This MUST be in the same order as the list returned by "labels".

    returns

    A list of numeric details corresponding to the labels (order must be preserved).

    Definition Classes
    ClassificationResult → CategoricalResult

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

    Definition Classes
    AnyRef

  11. def equals(other: MLResult, tolerance: Double = 0): Boolean

    Used in tests to compare results, within a given numerical tolerance range.

    Used in tests to compare results, within a given numerical tolerance range.

    Definition Classes
    ClassificationResult → CategoricalResult → MLResult

  12. def equals(obj: Any): Boolean

    Definition Classes
    CategoricalResult → AnyRef → Any

  13. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes
    AnyRef → Any

  15. lazy val index: Int

    Definition Classes
    ClassificationResult → CategoricalResult

  16. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  17. val labels: Seq[String]

    returns

    The list of potential labels that can be generated by the model. e.g. ["yes", "no"]

    Definition Classes
    ClassificationResult → CategoricalResult

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

    Definition Classes
    AnyRef

  19. final def notify(): Unit

    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

    Definition Classes
    AnyRef

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

    Definition Classes
    AnyRef

  22. lazy val value: String

    Definition Classes
    ClassificationResult → CategoricalResult → MLResult

  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
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from CategoricalResult

Inherited from MLResult

Inherited from AnyRef

Inherited from Any

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