com.eharmony.aloha.dataset.vw.multilabel

VwMultilabelRowCreator

final case class VwMultilabelRowCreator[-A, K](allLabelsInTrainingSet: IndexedSeq[K], featuresFunction: FeatureExtractorFunction[A, Sparse], defaultNamespace: List[Int], namespaces: List[(String, List[Int])], normalizer: Option[(CharSequence) ⇒ CharSequence], positiveLabelsFunction: GenAggFunc[A, IndexedSeq[K]], classNs: Char, dummyClassNs: Char, includeZeroValues: Boolean = false) extends RowCreator[A, Array[String]] with Product with Serializable

Creates training data for multilabel models in Vowpal Wabbit's CSOAA LDF and WAP LDF format for the JNI.

A

the input type

K

the label or class type

allLabelsInTrainingSet

all labels in the training set. This is a sequence because order matters. Order here can be chosen arbitrarily, but it must be consistent in the training and test formulation.

featuresFunction

features to extract from the data of type A.

defaultNamespace

list of feature indices in the default VW namespace.

namespaces

a mapping from VW namespace name to feature indices in that namespace.

normalizer

can modify VW output (currently unused)

positiveLabelsFunction

A method that can extract positive class labels.

classNs

the namespace name for class information.

dummyClassNs

the namespace name for dummy class information. 2 dummy classes are added to make the predicted probabilities work.

includeZeroValues

include zero values in VW input?

Since

9/13/2017

Linear Supertypes
Product, Equals, RowCreator[A, Array[String]], Serializable, Serializable, (A) ⇒ (MissingAndErroneousFeatureInfo, Array[String]), AnyRef, Any
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  1. VwMultilabelRowCreator
  2. Product
  3. Equals
  4. RowCreator
  5. Serializable
  6. Serializable
  7. Function1
  8. AnyRef
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Instance Constructors

  1. new VwMultilabelRowCreator(allLabelsInTrainingSet: IndexedSeq[K], featuresFunction: FeatureExtractorFunction[A, Sparse], defaultNamespace: List[Int], namespaces: List[(String, List[Int])], normalizer: Option[(CharSequence) ⇒ CharSequence], positiveLabelsFunction: GenAggFunc[A, IndexedSeq[K]], classNs: Char, dummyClassNs: Char, includeZeroValues: Boolean = false)

    allLabelsInTrainingSet

    all labels in the training set. This is a sequence because order matters. Order here can be chosen arbitrarily, but it must be consistent in the training and test formulation.

    featuresFunction

    features to extract from the data of type A.

    defaultNamespace

    list of feature indices in the default VW namespace.

    namespaces

    a mapping from VW namespace name to feature indices in that namespace.

    normalizer

    can modify VW output (currently unused)

    positiveLabelsFunction

    A method that can extract positive class labels.

    classNs

    the namespace name for class information.

    dummyClassNs

    the namespace name for dummy class information. 2 dummy classes are added to make the predicted probabilities work.

    includeZeroValues

    include zero values in VW input?

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. val allLabelsInTrainingSet: IndexedSeq[K]

    all labels in the training set.

    all labels in the training set. This is a sequence because order matters. Order here can be chosen arbitrarily, but it must be consistent in the training and test formulation.

  7. def andThen[A](g: ((MissingAndErroneousFeatureInfo, Array[String])) ⇒ A): (A) ⇒ A

    Definition Classes
    Function1
    Annotations
    @unspecialized()

  8. def apply(a: A): (MissingAndErroneousFeatureInfo, Array[String])

    Definition Classes
    VwMultilabelRowCreator → Function1

  9. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  10. val classNs: Char

    the namespace name for class information.

  11. def clone(): AnyRef

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

  12. def compose[A](g: (A) ⇒ A): (A) ⇒ (MissingAndErroneousFeatureInfo, Array[String])

    Definition Classes
    Function1
    Annotations
    @unspecialized()

  13. val defaultNamespace: List[Int]

    list of feature indices in the default VW namespace.

  14. val dummyClassNs: Char

    the namespace name for dummy class information.

    the namespace name for dummy class information. 2 dummy classes are added to make the predicted probabilities work.

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

    Definition Classes
    AnyRef

  16. val featuresFunction: FeatureExtractorFunction[A, Sparse]

    features to extract from the data of type A.

  17. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  19. val includeZeroValues: Boolean

    include zero values in VW input?

  20. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  21. val namespaces: List[(String, List[Int])]

    a mapping from VW namespace name to feature indices in that namespace.

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

    Definition Classes
    AnyRef

  23. val normalizer: Option[(CharSequence) ⇒ CharSequence]

    can modify VW output (currently unused)

  24. final def notify(): Unit

    Definition Classes
    AnyRef

  25. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  26. val positiveLabelsFunction: GenAggFunc[A, IndexedSeq[K]]

    A method that can extract positive class labels.

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

    Definition Classes
    AnyRef

  28. def toString(): String

    Definition Classes
    Function1 → AnyRef → Any

  29. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
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    Annotations
    @throws( ... )

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

    Definition Classes
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    Annotations
    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from RowCreator[A, Array[String]]

Inherited from Serializable

Inherited from Serializable

Inherited from (A) ⇒ (MissingAndErroneousFeatureInfo, Array[String])

Inherited from AnyRef

Inherited from Any

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