org.allenai.nlpstack.parse.poly.ml

WrapperClassifier

Related Docs: object WrapperClassifier | package ml

case class WrapperClassifier(classifier: ProbabilisticClassifier, featureNameMap: Seq[(Int, FeatureName)]) extends Product with Serializable

A WrapperClassifier wraps a ProbabilisticClassifier (which uses integer-based feature names) in an interface that allows you to use the more natural org.allenai.nlpstack.parse.poly.ml FeatureVector format for classification. This is a trait that specific wrappers can extend.

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Instance Constructors

  1. new WrapperClassifier(classifier: ProbabilisticClassifier, featureNameMap: Seq[(Int, FeatureName)])

Value Members

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

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

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

    Definition Classes
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  4. final def asInstanceOf[T0]: T0

    Definition Classes
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  5. val classifier: ProbabilisticClassifier

  6. def classify(featureVector: FeatureVector): (Int, Option[Justification])

    Returns the most probable (integer) outcome, given the input feature vector.

    Returns the most probable (integer) outcome, given the input feature vector.

    featureVector

    the feature vector to classify

    returns

    the most probable (integer) outcome

  7. def clone(): AnyRef

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    @throws( ... )

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

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  9. def featureNameForIndex(index: Int): FeatureName

    Returns a feature name based on an index.

    Returns a feature name based on an index.

    Attributes
    protected

  10. val featureNameMap: Seq[(Int, FeatureName)]

  11. val featureNameToIndex: Map[FeatureName, Int]

    The inverse of featureNameMap.

    The inverse of featureNameMap.

    Attributes
    protected

  12. def finalize(): Unit

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

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

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  14. def getDistribution(featureVector: FeatureVector): Map[Int, Float]

    Returns a distribution over all (integer) outcomes, given the input feature vector.

    Returns a distribution over all (integer) outcomes, given the input feature vector.

    featureVector

    the feature vector to classify

    returns

    the most probable (integer) outcome

  15. final def isInstanceOf[T0]: Boolean

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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

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  20. final def wait(): Unit

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

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

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