cc.factorie.app.nlp.ner.ChainNer

ChainNERModel

class ChainNERModel[Features <: CategoricalVectorVar[String]] extends ChainModel[L, Features, Token]

Linear Supertypes
ChainModel[L, Features, Token], model.Parameters, model.Model, AnyRef, Any
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  1. ChainNERModel
  2. ChainModel
  3. Parameters
  4. Model
  5. AnyRef
  6. Any
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Instance Constructors

  1. new ChainNERModel(featuresDomain: CategoricalVectorDomain[String], labelToFeatures: (L) ⇒ Features, labelToToken: (L) ⇒ Token, tokenToLabel: (Token) ⇒ L)(implicit mf: Manifest[Features])

Type Members

  1. class ChainLikelihoodExample extends optimize.Example

    Definition Classes
    ChainModel

  2. class ChainStructuredSVMExample extends ChainViterbiExample

    Definition Classes
    ChainModel

  3. class ChainViterbiExample extends optimize.Example

    Definition Classes
    ChainModel

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
    AnyRef → Any

  4. def Weights(t4: ⇒ Tensor4): Weights4

    Definition Classes
    Parameters

  5. def Weights(t3: ⇒ Tensor3): Weights3

    Definition Classes
    Parameters

  6. def Weights(t2: ⇒ Tensor2): Weights2

    Definition Classes
    Parameters

  7. def Weights(t1: ⇒ Tensor1): Weights1

    Definition Classes
    Parameters

  8. def accumulateExtraObsGradients(gradient: WeightsMapAccumulator, obsMarginal: la.Tensor1, position: Int, labels: Seq[L]): Unit

    Definition Classes
    ChainModel

  9. def addFactors(dl: variable.DiffList, result: Set[model.Factor]): Unit

    Append to "result" all Factors in this Model that are affected by the given DiffList.

    Append to "result" all Factors in this Model that are affected by the given DiffList. This method must not append duplicates.

    Definition Classes
    Model

  10. def addFactors(d: variable.Diff, result: Set[model.Factor]): Unit

    Append to "result" all Factors in this Model that are affected by the given Diff.

    Append to "result" all Factors in this Model that are affected by the given Diff. This method must not append duplicates.

    Definition Classes
    Model

  11. def addFactors(variable: variable.Var, result: Set[model.Factor]): Unit

    Append to "result" all Factors in this Model that touch the given "variable".

    Append to "result" all Factors in this Model that touch the given "variable". This method must not append duplicates.

    Definition Classes
    Model

  12. def addFactors(variables: Iterable[variable.Var], result: Set[model.Factor]): Unit

    Append to "result" all Factors in this Model that touch any of the given "variables".

    Append to "result" all Factors in this Model that touch any of the given "variables". This method must not append duplicates.

    Definition Classes
    Model

  13. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  14. def assignmentScore(dl: variable.DiffList, assignment: variable.Assignment): Double

    Definition Classes
    Model

  15. def assignmentScore(d: variable.Diff, assignment: variable.Assignment): Double

    Definition Classes
    Model

  16. def assignmentScore(vars: Iterable[variable.Var], assignment: variable.Assignment): Double

    Definition Classes
    Model

  17. def assignmentScore(variable: variable.Var, assignment: variable.Assignment): Double

    Definition Classes
    Model

  18. val bias: DotFamilyWithStatistics1[L] { val weights: cc.factorie.model.Weights1 }

    Definition Classes
    ChainModel

  19. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  20. def currentScore(dl: variable.DiffList): Double

    Definition Classes
    Model

  21. def currentScore(d: variable.Diff): Double

    Definition Classes
    Model

  22. def currentScore(vars: Iterable[variable.Var]): Double

    Definition Classes
    Model

  23. def currentScore(variable: variable.Var): Double

    Definition Classes
    Model

  24. def deserialize(stream: InputStream): Unit

    Definition Classes
    ChainModel

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

    Definition Classes
    AnyRef

  26. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  27. def factors(v: variable.Var): Iterable[model.Factor]

    Return all Factors in this Model that touch the given "variable".

    Return all Factors in this Model that touch the given "variable". The result will not have any duplicate Factors.

    Definition Classes
    ChainModel → Model

  28. def factors(variables: Iterable[variable.Var]): Iterable[model.Factor]

    Return all Factors in this Model that touch any of the given "variables".

    Return all Factors in this Model that touch any of the given "variables". The result will not have any duplicate Factors.

    Definition Classes
    ChainModel → Model

  29. def factors(dl: variable.DiffList): Iterable[model.Factor]

    Return all Factors in this Model that are affected by the given DiffList.

    Return all Factors in this Model that are affected by the given DiffList. The result will not have any duplicate Factors. By default returns just the factors that neighbor the DiffList.variables, but this method may be overridden for special handling of the DiffList

    Definition Classes
    Model

  30. def factors(d: variable.Diff): Iterable[model.Factor]

    Return all Factors in this Model that are affected by the given Diff.

    Return all Factors in this Model that are affected by the given Diff. The result will not have any duplicate Factors. By default returns just the factors that neighbor Diff.variable, but this method may be overridden for special handling of the Diff

    Definition Classes
    Model

  31. def factorsOfClass[F <: model.Factor](d: variable.DiffList)(implicit fm: ClassTag[F]): Iterable[F]

    Definition Classes
    Model

  32. def factorsOfClass[F <: model.Factor](d: variable.DiffList, fclass: Class[F]): Iterable[F]

    Definition Classes
    Model

  33. def factorsOfClass[F <: model.Factor](variables: Iterable[variable.Var])(implicit fm: ClassTag[F]): Iterable[F]

    Definition Classes
    Model

  34. def factorsOfClass[F <: model.Factor](variable: variable.Var)(implicit fm: ClassTag[F]): Iterable[F]

    Definition Classes
    Model

  35. def factorsOfClass[F <: model.Factor](variables: Iterable[variable.Var], fclass: Class[F]): Iterable[F]

    Definition Classes
    Model

  36. def factorsOfClass[F <: model.Factor](variable: variable.Var, fclass: Class[F]): Iterable[F]

    Definition Classes
    Model

  37. def factorsOfFamilies[F <: Family](d: variable.DiffList, families: Seq[F]): Iterable[model.Model.factorsOfFamilies.F.Factor]

    Definition Classes
    Model

  38. def factorsOfFamilies[F <: Family](variables: Iterable[variable.Var], families: Seq[F]): Iterable[model.Model.factorsOfFamilies.F.Factor]

    Definition Classes
    Model

  39. def factorsOfFamilies[F <: Family](variable: variable.Var, families: Seq[F]): Iterable[model.Model.factorsOfFamilies.F.Factor]

    Definition Classes
    Model

  40. def factorsOfFamily[F <: Family](d: variable.DiffList, family: F): Iterable[model.Model.factorsOfFamily.F.Factor]

    Definition Classes
    Model

  41. def factorsOfFamily[F <: Family](variables: Iterable[variable.Var], family: F): Iterable[model.Model.factorsOfFamily.F.Factor]

    Definition Classes
    Model

  42. def factorsOfFamily[F <: Family](variable: variable.Var, family: F): Iterable[model.Model.factorsOfFamily.F.Factor]

    Definition Classes
    Model

  43. def factorsOfFamilyClass[F <: Family](d: variable.DiffList)(implicit fm: ClassTag[F]): Iterable[model.Model.factorsOfFamilyClass.F.Factor]

    Definition Classes
    Model

  44. def factorsOfFamilyClass[F <: Family](d: variable.DiffList, fclass: Class[F]): Iterable[model.Model.factorsOfFamilyClass.F.Factor]

    Definition Classes
    Model

  45. def factorsOfFamilyClass[F <: Family](variables: Iterable[variable.Var])(implicit fm: ClassTag[F]): Iterable[model.Model.factorsOfFamilyClass.F.Factor]

    Definition Classes
    Model

  46. def factorsOfFamilyClass[F <: Family](variable: variable.Var)(implicit fm: ClassTag[F]): Iterable[model.Model.factorsOfFamilyClass.F.Factor]

    Definition Classes
    Model

  47. def factorsOfFamilyClass[F <: Family](variables: Iterable[variable.Var], fclass: Class[F]): Iterable[model.Model.factorsOfFamilyClass.F.Factor]

    Definition Classes
    Model

  48. def factorsOfFamilyClass[F <: Family](variable: variable.Var, fclass: Class[F]): Iterable[model.Model.factorsOfFamilyClass.F.Factor]

    Definition Classes
    Model

  49. val featureClass: Class[_]

    Definition Classes
    ChainModel

  50. val featuresDomain: CategoricalVectorDomain[String]

    Definition Classes
    ChainModel

  51. def filterByFactorClass[F <: model.Factor](factors: Iterable[model.Factor], fclass: Class[F]): Iterable[F]

    Definition Classes
    Model

  52. def filterByFamilies[F <: Family](factors: Iterable[model.Factor], families: Seq[F]): Iterable[model.Model.filterByFamilies.F.Factor]

    Definition Classes
    Model

  53. def filterByFamily[F <: Family](factors: Iterable[model.Factor], family: F): Iterable[model.Model.filterByFamily.F.Factor]

    Definition Classes
    Model

  54. def filterByFamilyClass[F <: Family](factors: Iterable[model.Factor], fclass: Class[F]): Iterable[model.Model.filterByFamilyClass.F.Factor]

    Definition Classes
    Model

  55. def filterByNotFamilyClass[F <: Family](factors: Iterable[model.Factor], fclass: Class[F]): Iterable[model.Factor]

    Definition Classes
    Model

  56. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes
    AnyRef → Any

  58. def getCliqueValues(varying: Seq[L], addToLocalScoresOpt: Option[Array[la.Tensor1]] = None): ChainCliqueValues

    Definition Classes
    ChainModel

  59. def getHammingLossScores(varying: Seq[L with LabeledMutableDiscreteVar]): Array[la.Tensor1]

    Definition Classes
    ChainModel

  60. def getLocalScores(varying: Seq[L]): Array[la.DenseTensor1]

    Definition Classes
    ChainModel

  61. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  62. def inferFast(varying: Seq[L], addToLocalScoresOpt: Option[Array[la.Tensor1]] = None): ChainForwardBackwardResults

    Definition Classes
    ChainModel

  63. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  64. def itemizedModel(dl: variable.DiffList): ItemizedModel

    Definition Classes
    Model

  65. def itemizedModel(d: variable.Diff): ItemizedModel

    Definition Classes
    Model

  66. def itemizedModel(variables: Iterable[variable.Var]): ItemizedModel

    Definition Classes
    Model

  67. def itemizedModel(variable: variable.Var): ItemizedModel

    Definition Classes
    Model

  68. val labelClass: Class[_]

    Definition Classes
    ChainModel

  69. val labelDomain: CategoricalDomain[String]

    Definition Classes
    ChainModel

  70. val labelToFeatures: (L) ⇒ Features

    Definition Classes
    ChainModel

  71. val labelToToken: (L) ⇒ Token

    Definition Classes
    ChainModel

  72. val markov: DotFamilyWithStatistics2[L, L] { val weights: cc.factorie.model.Weights2 }

    Definition Classes
    ChainModel

  73. def maximize(vars: Seq[L])(implicit d: variable.DiffList): Unit

    Definition Classes
    ChainModel

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

    Definition Classes
    AnyRef

  75. def newFactorsCollection: Set[model.Factor]

    The "factors" methods need a new collection to return; this method is used by them to construct this collection.

    The "factors" methods need a new collection to return; this method is used by them to construct this collection.

    Definition Classes
    Model

  76. final def notify(): Unit

    Definition Classes
    AnyRef

  77. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  78. val obs: DotFamilyWithStatistics2[Features, L] { val weights: cc.factorie.model.Weights2 }

    Definition Classes
    ChainModel

  79. val obsmarkov: DotFamilyWithStatistics3[L, L, Features] { val weights: cc.factorie.model.Weights3 }

    Definition Classes
    ChainModel

  80. val parameters: WeightsSet

    Definition Classes
    Parameters

  81. def serialize(stream: OutputStream): Unit

    Definition Classes
    ChainModel

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

    Definition Classes
    AnyRef

  83. def toString(): String

    Definition Classes
    AnyRef → Any

  84. val tokenClass: Class[_]

    Definition Classes
    ChainModel

  85. val tokenToLabel: (Token) ⇒ L

    Definition Classes
    ChainModel

  86. var useObsMarkov: Boolean

    Definition Classes
    ChainModel

  87. def viterbiFast(varying: Seq[L], addToLocalScoresOpt: Option[Array[la.Tensor1]] = None): ChainViterbiResults

    Definition Classes
    ChainModel

  88. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from ChainModel[L, Features, Token]

Inherited from model.Parameters

Inherited from model.Model

Inherited from AnyRef

Inherited from Any

Ungrouped