edu.stanford.nlp.tmt.model.llda

GibbsLabeledLDA

class GibbsLabeledLDA extends LabeledLDA[HardAssignmentModelState, GibbsLabeledLDADocument, (String, Array[Int])] with HardAssignmentModel[LabeledLDAModelParams, LabeledLDADocumentParams, GibbsLabeledLDADocument]

Labeled LDA with learning and inference via collapsed gibbs sampling.

Linear Supertypes
HardAssignmentModel[LabeledLDAModelParams, LabeledLDADocumentParams, GibbsLabeledLDADocument], LabeledLDA[HardAssignmentModelState, GibbsLabeledLDADocument, (String, Array[Int])], DirichletTopicSmoothing, DirichletTermSmoothing, ClosedTopicSet, TopicModel[LabeledLDAModelParams, HardAssignmentModelState, LabeledLDADocumentParams, GibbsLabeledLDADocument, (String, Array[Int])], RepCheck, Stateful[HardAssignmentModelState], AnyRef, Any
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Inherited
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  1. GibbsLabeledLDA
  2. HardAssignmentModel
  3. LabeledLDA
  4. DirichletTopicSmoothing
  5. DirichletTermSmoothing
  6. ClosedTopicSet
  7. TopicModel
  8. RepCheck
  9. Stateful
  10. AnyRef
  11. Any
Visibility
  1. Public
  2. All

Instance Constructors

  1. new GibbsLabeledLDA (params: LabeledLDAModelParams, seed: Long, inferParams: GibbsInferParams, log: (String) ⇒ Unit)

Value Members

  1. def != (arg0: AnyRef): Boolean

    Attributes
    final
    Definition Classes
    AnyRef

  2. def != (arg0: Any): Boolean

    Attributes
    final
    Definition Classes
    Any

  3. def ## (): Int

    Attributes
    final
    Definition Classes
    AnyRef → Any

  4. def == (arg0: AnyRef): Boolean

    Attributes
    final
    Definition Classes
    AnyRef

  5. def == (arg0: Any): Boolean

    Attributes
    final
    Definition Classes
    Any

  6. def asGibbsLDA : GibbsLDA

  7. def asInstanceOf [T0] : T0

    Attributes
    final
    Definition Classes
    Any

  8. var checkers : List[Function0[_]]

    Attributes
    protected
    Definition Classes
    RepCheck

  9. def checkrep (): Unit

    Assert invariants.

    Assert invariants.

    Attributes
    protected final
    Definition Classes
    RepCheck

  10. def clone (): AnyRef

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

  11. val countTopic : Array[Int]

    How many times each topic is seen overall.

    How many times each topic is seen overall.

    Definition Classes
    HardAssignmentModel

  12. val countTopicTerm : Array[Array[Int]]

    How many times each term is seen in each topic.

    How many times each term is seen in each topic.

    Definition Classes
    HardAssignmentModel

  13. def create (dp: LabeledLDADocumentParams): GibbsLabeledLDADocument

    Creates a document from the given document parameters.

    Creates a document from the given document parameters.

    Definition Classes
    GibbsLabeledLDA → TopicModel

  14. def eq (arg0: AnyRef): Boolean

    Attributes
    final
    Definition Classes
    AnyRef

  15. def equals (arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  16. def finalize (): Unit

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

  17. def getClass (): java.lang.Class[_]

    Attributes
    final
    Definition Classes
    AnyRef → Any

  18. def getTopicTermDistribution (topic: String): Array[Double]

    Returns the distribution over terms for the given topic.

    Returns the distribution over terms for the given topic. The return value of this method is assumed to have already incorporated the corresponding getTermSmoothing to the appropriate extent.

    Attributes
    final
    Definition Classes
    ClosedTopicSet

  19. def getTopicTermDistribution (topic: Int): Array[Double]

    Returns the distribution over terms for the given topic.

    Returns the distribution over terms for the given topic. The return value of this method is assumed to have already incorporated the corresponding getTermSmoothing to the appropriate extent.

    Definition Classes
    ClosedTopicSet

  20. def hashCode (): Int

    Definition Classes
    AnyRef → Any

  21. def infer (doc: GibbsLabeledLDADocument): SparseArray[Double]

    Does inference on the given document until convergence.

    Does inference on the given document until convergence.

    Definition Classes
    GibbsLabeledLDA → LabeledLDA

  22. def infer (doc: String, labels: Array[String]): SparseArray[Double]

    Does inference on the given document until convergence.

    Does inference on the given document until convergence.

    Definition Classes
    LabeledLDA

  23. def infer (doc: LabeledLDADocumentParams): SparseArray[Double]

    Does inference on the given document until convergence.

    Does inference on the given document until convergence.

    Definition Classes
    LabeledLDA

  24. val inferParams : GibbsInferParams

  25. def inferSampler : InferSampler

    Gets a thread-local inference sampler.

  26. val inferSamplerTL : ThreadLocal[InferSampler]

    Attributes
    protected

  27. def isInstanceOf [T0] : Boolean

    Attributes
    final
    Definition Classes
    Any

  28. val learnSampler : LearnSampler

  29. val log : (String) ⇒ Unit

    Where log messages go.

    Where log messages go. Defaults to System.err.println.

    Definition Classes
    GibbsLabeledLDA → TopicModel

  30. def ne (arg0: AnyRef): Boolean

    Attributes
    final
    Definition Classes
    AnyRef

  31. def notify (): Unit

    Attributes
    final
    Definition Classes
    AnyRef

  32. def notifyAll (): Unit

    Attributes
    final
    Definition Classes
    AnyRef

  33. val numTerms : Int

    The number of terms in the model.

    The number of terms in the model.

    Definition Classes
    LabeledLDA → TopicModel

  34. val numTopics : Int

    The number of topics in the model.

    The number of topics in the model.

    Definition Classes
    LabeledLDA → ClosedTopicSet

  35. def pTopicTerm (topic: Int, term: Int): Double

    Returns the probability of the given term in the given topic.

    Returns the probability of the given term in the given topic.

    Attributes
    final
    Definition Classes
    HardAssignmentModel → ClosedTopicSet

  36. def pTopicTerm (topic: String, term: String): Double

    Returns the probability of the given term in the given topic.

    Returns the probability of the given term in the given topic.

    Definition Classes
    ClosedTopicSet

  37. val params : LabeledLDAModelParams

    The parameters used to create this model.

    The parameters used to create this model.

    Definition Classes
    GibbsLabeledLDA → LabeledLDA → TopicModel

  38. def registerCheck (check: Function0[_]): Unit

    Registers a function as a checker of invariants.

    Registers a function as a checker of invariants.

    Attributes
    protected
    Definition Classes
    RepCheck

  39. def reset (): Unit

    Resets to the default state.

    Resets to the default state.

    Definition Classes
    HardAssignmentModel → Stateful

  40. def sampleInfer (doc: GibbsLabeledLDADocument): Unit

  41. def sampleLearn (doc: GibbsLabeledLDADocument): Unit

  42. val seed : Long

  43. def state : HardAssignmentModelState

    Gets the current state of this object.

    Gets the current state of this object.

    Definition Classes
    HardAssignmentModel → Stateful

  44. def state_= (state: HardAssignmentModelState): Unit

    Sets the current state of this object.

    Sets the current state of this object.

    Definition Classes
    HardAssignmentModel → Stateful

  45. def summary : Iterator[String]

    Returns human-readable summary of the current topic model.

    Returns human-readable summary of the current topic model.

    Definition Classes
    HardAssignmentModel

  46. def synchronized [T0] (arg0: ⇒ T0): T0

    Attributes
    final
    Definition Classes
    AnyRef

  47. def termIndex : Option[Index[String]]

    The term index describing which terms are in the model.

    The term index describing which terms are in the model.

    Attributes
    final
    Definition Classes
    TopicModel

  48. def termIndex_= (index: Option[Index[String]]): Unit

    Attributes
    protected final
    Definition Classes
    TopicModel

  49. def termSmoothDenom : Double

    Attributes
    protected
    Definition Classes
    DirichletTermSmoothing

  50. def termSmoothing : Array[Double]

    Add-k prior counts for each term (eta in the model formulation).

    Add-k prior counts for each term (eta in the model formulation).

    Attributes
    final
    Definition Classes
    DirichletTermSmoothing

  51. def termSmoothing_= (smoothing: Array[Double]): Unit

    Attributes
    protected
    Definition Classes
    DirichletTermSmoothing

  52. def toString (): String

    Definition Classes
    AnyRef → Any

  53. def tokenize (document: String): Iterable[Int]

    Tokenizes the given input string using our stored tokenizer and term index, if available.

    Tokenizes the given input string using our stored tokenizer and term index, if available. Otherwise, throws an IllegalArgumentException.

    Attributes
    protected
    Definition Classes
    TopicModel

  54. def tokenizer : Option[Tokenizer]

    The tokenizer used to break input documents into terms.

    The tokenizer used to break input documents into terms.

    Attributes
    final
    Definition Classes
    TopicModel

  55. def tokenizer_= (tokenizer: Option[Tokenizer]): Unit

    Attributes
    protected final
    Definition Classes
    TopicModel

  56. var topicIndex : Option[Index[String]]

    The term index describing which terms are in the model.

    The term index describing which terms are in the model.

    Definition Classes
    ClosedTopicSet

  57. def topicName (topic: Int): String

    Gets the name for this topic.

    Gets the name for this topic.

    Definition Classes
    ClosedTopicSet

  58. def topicSmoothing : Array[Double]

    Prior counts for each topic (alpha in the model formulation).

    Prior counts for each topic (alpha in the model formulation).

    Attributes
    final
    Definition Classes
    DirichletTopicSmoothing

  59. def topicSmoothing_= (smoothing: Array[Double]): Unit

    Attributes
    protected
    Definition Classes
    DirichletTopicSmoothing

  60. def wait (): Unit

    Attributes
    final
    Definition Classes
    AnyRef
    Annotations
    @throws()

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

    Attributes
    final
    Definition Classes
    AnyRef
    Annotations
    @throws()

  62. def wait (arg0: Long): Unit

    Attributes
    final
    Definition Classes
    AnyRef
    Annotations
    @throws()

Inherited from HardAssignmentModel[LabeledLDAModelParams, LabeledLDADocumentParams, GibbsLabeledLDADocument]

Inherited from LabeledLDA[HardAssignmentModelState, GibbsLabeledLDADocument, (String, Array[Int])]

Inherited from DirichletTopicSmoothing

Inherited from DirichletTermSmoothing

Inherited from ClosedTopicSet

Inherited from TopicModel[LabeledLDAModelParams, HardAssignmentModelState, LabeledLDADocumentParams, GibbsLabeledLDADocument, (String, Array[Int])]

Inherited from RepCheck

Inherited from Stateful[HardAssignmentModelState]

Inherited from AnyRef

Inherited from Any