org.apache.spark.mllib.evaluation

BinaryClassificationMetrics

class BinaryClassificationMetrics extends Logging

:: Experimental :: Evaluator for binary classification.

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@Experimental()
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Instance Constructors

  1. new BinaryClassificationMetrics(scoreAndLabels: RDD[(Double, Double)])

    scoreAndLabels

    an RDD of (score, label) pairs.

Value Members

  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 areaUnderPR(): Double

    Computes the area under the precision-recall curve.

  5. def areaUnderROC(): Double

    Computes the area under the receiver operating characteristic (ROC) curve.

  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def fMeasureByThreshold(): RDD[(Double, Double)]

    Returns the (threshold, F-Measure) curve with beta = 1.0.

  11. def fMeasureByThreshold(beta: Double): RDD[(Double, Double)]

    Returns the (threshold, F-Measure) curve.

    Returns the (threshold, F-Measure) curve.

    beta

    the beta factor in F-Measure computation.

    returns

    an RDD of (threshold, F-Measure) pairs.

    See also

    http://en.wikipedia.org/wiki/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. def isTraceEnabled(): Boolean

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  17. def log: Logger

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  18. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  19. def logDebug(msg: ⇒ String): Unit

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  20. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  21. def logError(msg: ⇒ String): Unit

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  22. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  23. def logInfo(msg: ⇒ String): Unit

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  24. def logName: String

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  25. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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  26. def logTrace(msg: ⇒ String): Unit

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  27. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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  28. def logWarning(msg: ⇒ String): Unit

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

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  30. final def notify(): Unit

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  31. final def notifyAll(): Unit

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  32. def pr(): RDD[(Double, Double)]

    Returns the precision-recall curve, which is an RDD of (recall, precision), NOT (precision, recall), with (0.0, 1.0) prepended to it.

    Returns the precision-recall curve, which is an RDD of (recall, precision), NOT (precision, recall), with (0.0, 1.0) prepended to it.

    See also

    http://en.wikipedia.org/wiki/Precision_and_recall

  33. def precisionByThreshold(): RDD[(Double, Double)]

    Returns the (threshold, precision) curve.

  34. def recallByThreshold(): RDD[(Double, Double)]

    Returns the (threshold, recall) curve.

  35. def roc(): RDD[(Double, Double)]

    Returns the receiver operating characteristic (ROC) curve, which is an RDD of (false positive rate, true positive rate) with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.

    Returns the receiver operating characteristic (ROC) curve, which is an RDD of (false positive rate, true positive rate) with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.

    See also

    http://en.wikipedia.org/wiki/Receiver_operating_characteristic

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

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  37. def thresholds(): RDD[Double]

    Returns thresholds in descending order.

  38. def toString(): String

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  39. def unpersist(): Unit

    Unpersist intermediate RDDs used in the computation.

  40. final def wait(): Unit

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

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

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