ClusteringResult

Value Members

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

   

   Definition Classes

   AnyRef → Any

2. final def ##(): Int

   

   Definition Classes

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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

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   Annotations

   @throws( ... )

6. 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

   ClusteringResult → CategoricalResult

7. val distances: Array[Double]

   

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

   

   Definition Classes

   AnyRef

9. def equals(other: MLResult, tolerance: Double): 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

   ClusteringResult → CategoricalResult → MLResult

10. def equals(obj: Any): Boolean

    

    Definition Classes

    CategoricalResult → AnyRef → Any

11. def finalize(): Unit

    

    Attributes

    protected[java.lang]

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

    

    Definition Classes

    AnyRef → Any

13. lazy val index: Int

    
    returns

    The index by which the prediction value may be found in the list of labels.

    Definition Classes

    ClusteringResult → CategoricalResult

14. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

15. val labels: Seq[String]

    
    returns

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

    Definition Classes

    ClusteringResult → CategoricalResult

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

    

    Definition Classes

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17. final def notify(): Unit

    

    Definition Classes

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18. final def notifyAll(): Unit

    

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

    

    Definition Classes

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20. def toMap: Map[String, Double]

    

    Definition Classes

    CategoricalResult

21. lazy val value: String

    
    returns

    The simple value of the prediction. e.g. "yes" or "1".

    Definition Classes

    ClusteringResult → CategoricalResult → MLResult

22. final def wait(): Unit

    

    Definition Classes

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    @throws( ... )

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

    

    Definition Classes

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    @throws( ... )

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

    

    Definition Classes

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    @throws( ... )