org.apache.mahout.classifier.stats

ConfusionMatrix

class ConfusionMatrix extends AnyRef

Ported from org.apache.mahout.classifier.ConfusionMatrix.java

The ConfusionMatrix Class stores the result of Classification of a Test Dataset.

The fact of whether there is a default is not stored. A row of zeros is the only indicator that there is no default.

See http://en.wikipedia.org/wiki/Confusion_matrix for background

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Instance Constructors

  1. new ConfusionMatrix(labels: Collection[String] = null, defaultLabel: String = "unknown")

    labels

    The labels to consider for classification

    defaultLabel

    default unknown label

Value Members

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

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

    Definition Classes
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  3. final def ##(): Int

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

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

    Definition Classes
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  6. def addInstance(correctLabel: String, classifiedLabel: String): Unit

  7. def addInstance(correctLabel: String, classifiedResult: ClassifierResult): Unit

  8. final def asInstanceOf[T0]: T0

    Definition Classes
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  9. def clone(): AnyRef

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

  10. var confusionMatrix: Array[Array[Int]]

    Matrix Constructor

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

    Definition Classes
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  12. def equals(arg0: Any): Boolean

    Definition Classes
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  13. def finalize(): Unit

    Attributes
    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

  14. def getAccuracy: Double

  15. def getAccuracy(label: String): Double

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

    Definition Classes
    AnyRef → Any

  17. def getConfusionMatrix: Array[Array[Int]]

  18. def getCorrect(label: String): Int

  19. def getCount(correctLabel: String, classifiedLabel: String): Int

  20. def getDefaultLabel: String

  21. def getF1score(label: String): Double

  22. def getKappa: Double

    Accuracy v.

    Accuracy v.s. randomly classifying all samples. kappa() = (totalAccuracy() - randomAccuracy()) / (1 - randomAccuracy()) Cohen, Jacob. 1960. A coefficient of agreement for nominal scales. Educational And Psychological Measurement 20:37-46.

    Formula and variable names from: http://www.yale.edu/ceo/OEFS/Accuracy.pdf

    returns

    double

  23. def getLabels: List[String]

  24. def getMatrix: Matrix

  25. def getNormalizedStats: RunningAverageAndStdDev

    Standard deviation of normalized producer accuracy Not a standard score

    Standard deviation of normalized producer accuracy Not a standard score

    returns

    double

  26. def getPrecision(label: String): Double

  27. def getRecall(label: String): Double

  28. def getReliability: Double

  29. def getSmallLabel(i: Int): String

  30. def getTotal(label: String): Int

  31. def getWeightedF1score: Double

  32. def getWeightedPrecision: Double

  33. def getWeightedRecall: Double

  34. def hashCode(): Int

    Definition Classes
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  35. var i: Integer

  36. def incrementCount(correctLabel: String, classifiedLabel: String): Unit

  37. def incrementCount(correctLabel: String, classifiedLabel: String, count: Int): Unit

  38. final def isInstanceOf[T0]: Boolean

    Definition Classes
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  39. val labelMap: HashMap[String, Integer]

  40. def merge(b: ConfusionMatrix): ConfusionMatrix

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

    Definition Classes
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  42. final def notify(): Unit

    Definition Classes
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  43. final def notifyAll(): Unit

    Definition Classes
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  44. def numLabels: Int

  45. def putCount(correctLabel: String, classifiedLabel: String, count: Int): Unit

  46. var samples: Int

  47. def setMatrix(m: Matrix): Unit

  48. def sortLabels(labels: Map[String, Integer]): Array[String]

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

    Definition Classes
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  50. def toString(): String

    This is overloaded.

    This is overloaded. toString() is not a formatted report you print for a manager :) Assume that if there are no default assignments, the default feature was not used

    Definition Classes
    ConfusionMatrix → AnyRef → Any

  51. def verifyLabels(length: Int, sorted: Array[String]): Unit

  52. final def wait(): Unit

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

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

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