org.allenai.nlpstack.parse.poly.ml

LinearModel

Related Docs: object LinearModel | package ml

case class LinearModel(coefficients: Seq[(FeatureName, Double)]) extends Product with Serializable

A weighted linear combination of features.

coefficients

map from feature names to weight coefficients

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Instance Constructors

  1. new LinearModel(coefficients: Seq[(FeatureName, Double)])

    coefficients

    map from feature names to weight coefficients

Value Members

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

    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Definition Classes
    AnyRef → Any

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

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

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  5. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )

  6. val coefficientMap: Map[FeatureName, Double]

  7. val coefficients: Seq[(FeatureName, Double)]

    map from feature names to weight coefficients

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

    Definition Classes
    AnyRef

  9. def finalize(): Unit

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

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

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  11. def getCoefficient(featureName: FeatureName): Double

    Returns the coefficient corresponding to the specified feature name.

    Returns the coefficient corresponding to the specified feature name.

    For unspecified coefficients, zero is returned.

    featureName

    the feature name of interest

    returns

    the coefficient corresponding to the specified feature name

  12. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  14. final def notify(): Unit

    Definition Classes
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  15. final def notifyAll(): Unit

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  16. def score(featureVector: FeatureVector): Double

    Computes the weighted linear combination, given the feature values in the argument vector.

    Computes the weighted linear combination, given the feature values in the argument vector.

    featureVector

    the feature vector of interest

    returns

    the weighted linear combination

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

    Definition Classes
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  18. final def wait(): Unit

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    @throws( ... )

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

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

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