sampleclean.activeml

DedupDemo

object DedupDemo

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

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

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  3. final def ##(): Int

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

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

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  6. val activeLearningAlgorithm: ActiveSVMWithSGD[DeduplicationPointLabelingContext, DeduplicationGroupLabelingContext]

  7. final def asInstanceOf[T0]: T0

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  8. def clone(): AnyRef

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  9. val conf: SparkConf

  10. val crowdParameters: CrowdConfiguration

  11. val crowdTask: DeduplicationTask

  12. val dedupGroupContext: DeduplicationGroupLabelingContext

  13. val emptyLabeledRDD: RDD[(String, LabeledPoint)]

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

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  15. def equals(arg0: Any): Boolean

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  16. def error(confusionMatrix: (Double, Double, Double, Double)): Double

    Compute error rate (1 - accuracy), which is (TP + TN) / (P + N)

    Compute error rate (1 - accuracy), which is (TP + TN) / (P + N)

    confusionMatrix

    the confusion matrix, a tuple of doubles for (TP, TN, FP, FN)

    returns

    the error rate as a double.

  17. def f1(confusionMatrix: (Double, Double, Double, Double)): Double

    Compute F-measure, which is 2TP / (2TP + FP + FN)

    Compute F-measure, which is 2TP / (2TP + FP + FN)

    confusionMatrix

    the confusion matrix, a tuple of doubles for (TP, TN, FP, FN)

    returns

    the F-measure as a Double.

  18. def finalize(): Unit

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  19. val frameworkParameters: ActiveLearningParameters

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

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  21. def hashCode(): Int

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  22. final def isInstanceOf[T0]: Boolean

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  23. def main(args: Array[String]): Unit

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

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  25. final def notify(): Unit

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  26. final def notifyAll(): Unit

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  27. val pointSelector: SVMMarginDistanceFilter[DeduplicationPointLabelingContext]

  28. def precision(confusionMatrix: (Double, Double, Double, Double)): Double

    Compute precision, which is TP / (TP + FP)

    Compute precision, which is TP / (TP + FP)

    confusionMatrix

    the confusion matrix, a tuple of doubles for (TP, TN, FP, FN)

    returns

    the precision as a Double.

  29. def processNewLabeledData(newData: RDD[(String, Double)]): Unit

  30. def processNewModel(model: SVMModel, modelN: Long): Unit

  31. def recall(confusionMatrix: (Double, Double, Double, Double)): Double

    Compute recall, which is TP / (TP + FN)

    Compute recall, which is TP / (TP + FN)

    confusionMatrix

    the confusion matrix, a tuple of doubles for (TP, TN, FP, FN)

    returns

    the recall as a Double.

  32. val sc: SparkContext

  33. val svmParameters: SVMParameters

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

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  35. val taskParameters: CrowdTaskConfiguration

  36. var testData: RDD[(String, LabeledPoint)]

  37. var testN: Long

  38. def toString(): String

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  39. var trainN: Long

  40. var trainingData: RDD[(String, LabeledPoint, DeduplicationPointLabelingContext)]

  41. final def wait(): Unit

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

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

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