Trait

epic.framework

AugmentableInference

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trait AugmentableInference[Datum, Augment] extends Inference[Datum]

AugmentableInference is an epic.framework.Inference that can support injecting additional information into the structure computation. This can include prior information over the structure (useful for EP or other Bayesian inference) or loss-augmentation.

Datum

the kind of thing to do inference on

Augment

the extra piece of information we can use to do inference

Linear Supertypes
Inference[Datum], Serializable, Serializable, AnyRef, Any
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Type Members

  1. abstract type Marginal <: framework.Marginal

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    Definition Classes
    Inference
  2. abstract type Scorer

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    Definition Classes
    Inference

Abstract Value Members

  1. abstract def baseAugment(v: Datum): Augment

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    The "no prior information" augment.

    The "no prior information" augment. Used if nothing is passed in.

  2. abstract def goldMarginal(scorer: Scorer, v: Datum, aug: Augment): Marginal

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  3. abstract def marginal(scorer: Scorer, v: Datum, aug: Augment): Marginal

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  4. abstract def scorer(v: Datum): Scorer

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    Definition Classes
    AugmentableInferenceInference

Concrete Value Members

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

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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

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

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    Any
  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    AnyRef
    Annotations
    @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  8. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  9. def forTesting: AugmentableInference[Datum, Augment]

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

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    Definition Classes
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  11. def goldMarginal(scorer: Scorer, v: Datum): Marginal

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    Produces the "gold marginal" which is the marginal conditioned on the output label/structure itself.

    Produces the "gold marginal" which is the marginal conditioned on the output label/structure itself.

    v

    the example

    returns

    gold marginal

    Definition Classes
    AugmentableInferenceInference
  12. def hashCode(): Int

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    Definition Classes
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  13. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  14. def marginal(scorer: Scorer, v: Datum): Marginal

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    Produces the "guess marginal" which is the marginal conditioned on only the input data

    Produces the "guess marginal" which is the marginal conditioned on only the input data

    v

    the example

    returns

    gold marginal

    Definition Classes
    AugmentableInferenceInference
  15. def marginal(v: Datum): Marginal

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    Definition Classes
    Inference
  16. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  17. final def notify(): Unit

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    Definition Classes
    AnyRef
  18. final def notifyAll(): Unit

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

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    Definition Classes
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  20. def toString(): String

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  21. final def wait(): Unit

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    Annotations
    @throws( ... )
  22. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
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    @throws( ... )
  23. final def wait(arg0: Long): Unit

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    Definition Classes
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    @throws( ... )

Inherited from Inference[Datum]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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