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.

classifier

the embedded classifier (which uses integer-based feature names)

featureNameMap

a map from the integer feature names to their string-based form

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Instance Constructors

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

    classifier

    the embedded classifier (which uses integer-based feature names)

    featureNameMap

    a map from the integer feature names to their string-based form

Value Members

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

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    AnyRef → Any

  2. final def ##(): Int

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

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  4. final def asInstanceOf[T0]: T0

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  5. val classifier: ProbabilisticClassifier

    the embedded classifier (which uses integer-based feature names)

  6. def classify(featureVector: FeatureVector): Int

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

    a map from the integer feature names to their string-based form

  10. def finalize(): Unit

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

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

    Definition Classes
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  12. def getDistribution(featureVector: FeatureVector): Map[Int, Float]

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

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

    featureVector

    the feature vector to classify

    returns

    the most probable (integer) outcome

  13. final def isInstanceOf[T0]: Boolean

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

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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

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  18. final def wait(): Unit

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

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

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