Object

com.salesforce.op.evaluators.Evaluators

MultiClassification

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object MultiClassification

Factory that performs the evaluation of metrics for Binary Classification The metrics returned are Precision, Recall, F1 and Error Rate

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

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  2. final def ##(): Int

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

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  4. def apply(): OpMultiClassificationEvaluator

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    default: F1 Score

  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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  7. def custom(metricName: String, largerBetter: Boolean = true, evaluateFn: (Dataset[(Double, Vector, Vector, Double)]) ⇒ Double): OpMultiClassificationEvaluatorBase[SingleMetric]

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    Custom multiclass evaluator

    Custom multiclass evaluator

    metricName

    name of default metric

    evaluateFn

    evaluate function:

    • input: dataset consisting of four columns: (label, raw prediction, probability, prediction)
    • output: a single metric value Note: it the user's responsibility to take care of all the error scenarios in evaluateFn
    returns

    a new multiclass evaluator

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

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  9. def equals(arg0: Any): Boolean

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  10. def error(): OpMultiClassificationEvaluator

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    Prediction Error

  11. def f1(): OpMultiClassificationEvaluator

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    F1 Score

  12. def finalize(): Unit

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

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. def precision(): OpMultiClassificationEvaluator

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    Weighted Precision

  20. def recall(): OpMultiClassificationEvaluator

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    Weighted Recall

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

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  22. def toString(): String

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  23. final def wait(): Unit

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

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

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