org.apache.spark.streamdm.classifiers.trees

NominalFeatureClassObserver

class NominalFeatureClassObserver extends FeatureClassObserver with Serializable

Class for observing the class distribution of a nominal feature. The observer monitors the class distribution of a given feature. Used in Naive Bayes and decision trees to monitor data statistics on leaves.

Linear Supertypes
FeatureClassObserver, Serializable, Serializable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. NominalFeatureClassObserver
  2. FeatureClassObserver
  3. Serializable
  4. Serializable
  5. AnyRef
  6. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new NominalFeatureClassObserver(that: NominalFeatureClassObserver)

  2. new NominalFeatureClassObserver(numClasses: Int, fIndex: Int, numFeatureValues: Int, laplaceSmoothingFactor: Int = 1)

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def bestSplit(criterion: SplitCriterion, pre: Array[Double], fValue: Double, isBinarySplit: Boolean): FeatureSplit

    Gets the best split suggestion given a criterion and a class distribution

    Gets the best split suggestion given a criterion and a class distribution

    criterion

    the split criterion to use

    pre

    the class distribution before the split

    fValue

    the value of the feature

    isBinarySplit

    true to use binary splits

    returns

    suggestion of best feature split

    Definition Classes
    NominalFeatureClassObserver → FeatureClassObserver

  8. var blockClassFeatureStatistics: Array[Array[Double]]

  9. var blockWeight: Double

  10. var classFeatureStatistics: Array[Array[Double]]

  11. def clone(): AnyRef

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

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

    Definition Classes
    AnyRef

  13. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  14. val fIndex: Int

  15. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  17. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  18. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  19. val laplaceSmoothingFactor: Int

  20. def merge(that: FeatureClassObserver, trySplit: Boolean): FeatureClassObserver

    Merge the FeatureClassObserver to current FeatureClassObserver

    Merge the FeatureClassObserver to current FeatureClassObserver

    that

    the FeatureClassObserver will be merged

    trySplit

    whether called when a Hoeffding tree try to split

    returns

    current FeatureClassObserver

    Definition Classes
    NominalFeatureClassObserver → FeatureClassObserver

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

    Definition Classes
    AnyRef

  22. final def notify(): Unit

    Definition Classes
    AnyRef

  23. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  24. val numClasses: Int

  25. val numFeatureValues: Int

  26. def observeClass(cIndex: Double, fValue: Double, weight: Double): Unit

    Updates statistics of this observer given a feature value, a class index and the weight of the example observed

    Updates statistics of this observer given a feature value, a class index and the weight of the example observed

    cIndex

    the index of class

    fValue

    the value of the feature

    weight

    the weight of the example

    Definition Classes
    NominalFeatureClassObserver → FeatureClassObserver

  27. def observeTarget(fValue: Double, weight: Double): Unit

    Not yet supported.

    Not yet supported.

    Definition Classes
    FeatureClassObserver

  28. def probability(cIndex: Double, fValue: Double): Double

    Gets the probability for an attribute value given a class

    Gets the probability for an attribute value given a class

    cIndex

    the index of class

    fValue

    the value of the feature

    returns

    probability for a feature value given a class

    Definition Classes
    NominalFeatureClassObserver → FeatureClassObserver

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

    Definition Classes
    AnyRef

  30. def toString(): String

    Definition Classes
    AnyRef → Any

  31. var totalWeight: Double

  32. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from FeatureClassObserver

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped