class CRFInference[L, W] extends AugmentableInference[TaggedSequence[L, W], Anchoring[L, W]] with CRF[L, W] with AnnotatingInference[TaggedSequence[L, W]] with Serializable
- Annotations
- @SerialVersionUID()
Linear Supertypes
Ordering
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Inherited
- CRFInference
- AnnotatingInference
- CRF
- AugmentableInference
- Inference
- Serializable
- Serializable
- AnyRef
- Any
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Visibility
- Public
- All
Instance Constructors
- new CRFInference(weights: DenseVector[Double], featureIndex: Index[Feature], lexicon: Factory[L, W], featurizer: IndexedFeaturizer[L, W])
Type Members
- class Anchoring extends CRF.Anchoring[L, W]
- type ExpectedCounts = StandardExpectedCounts[Feature]
-
type
Marginal = CRF.Marginal[L, W]
- Definition Classes
- CRFInference → Inference
-
type
Scorer = CRF.Anchoring[L, W]
- Definition Classes
- CRFInference → Inference
Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
anchor(w: IndexedSeq[W]): Anchoring
- Definition Classes
- CRFInference → CRF
-
def
annotate(datum: TaggedSequence[L, W], m: Marginal): TaggedSequence[L, W]
- Definition Classes
- CRFInference → AnnotatingInference
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final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
def
baseAugment(v: TaggedSequence[L, W]): CRF.Anchoring[L, W]
The "no prior information" augment.
The "no prior information" augment. Used if nothing is passed in.
- Definition Classes
- CRFInference → AugmentableInference
-
def
bestSequence(w: IndexedSeq[W], id: String = ""): TaggedSequence[L, W]
- Definition Classes
- CRF
-
def
clone(): AnyRef
- Attributes
- protected[java.lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
- def emptyCounts: StandardExpectedCounts[Feature]
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
equals(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- val featureIndex: Index[Feature]
-
def
finalize(): Unit
- Attributes
- protected[java.lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
def
forTesting: AugmentableInference[TaggedSequence[L, W], CRF.Anchoring[L, W]]
- Definition Classes
- AugmentableInference → Inference
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
-
def
goldMarginal(scorer: Scorer, v: TaggedSequence[L, W], aug: CRF.Anchoring[L, W]): Marginal
- Definition Classes
- CRFInference → AugmentableInference
-
def
goldMarginal(tags: IndexedSeq[L], w: IndexedSeq[W]): CRF.Marginal[L, W]
- Definition Classes
- CRF
-
def
goldMarginal(scorer: Scorer, v: TaggedSequence[L, W]): Marginal
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
- AugmentableInference → Inference
-
def
hashCode(): Int
- Definition Classes
- AnyRef → Any
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final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
def
labelIndex: Index[L]
- Definition Classes
- CRFInference → CRF
- val lexicon: Factory[L, W]
-
def
marginal(scorer: Scorer, v: TaggedSequence[L, W], aug: CRF.Anchoring[L, W]): CRF.Marginal[L, W]
- Definition Classes
- CRFInference → AugmentableInference
-
def
marginal(w: IndexedSeq[W]): CRF.Marginal[L, W]
- Definition Classes
- CRF
-
def
marginal(scorer: Scorer, v: TaggedSequence[L, W]): Marginal
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
- AugmentableInference → Inference
-
def
marginal(v: TaggedSequence[L, W]): Marginal
- Definition Classes
- Inference
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- def posteriorDecode(m: Marginal): TaggedSequence[L, W]
-
def
scorer(v: TaggedSequence[L, W]): Scorer
- Definition Classes
- CRFInference → AugmentableInference → Inference
-
def
startSymbol: L
- Definition Classes
- CRFInference → CRF
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
def
toString(): String
- Definition Classes
- AnyRef → Any
- def viterbi(sentence: IndexedSeq[W], anchoring: CRF.Anchoring[L, W]): TaggedSequence[L, W]
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
- val weights: DenseVector[Double]