edu.stanford.nlp.tmt.model.lda.GibbsLDA

LearnSampler

class LearnSampler extends Sampler

A sampler that updates the model (normal gibbs sampling).

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  1. LearnSampler
  2. Sampler
  3. HardAssignmentGibbsSampler
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Instance Constructors

  1. new LearnSampler (countTopicTerm: Array[Array[Int]], countTopic: Array[Int], termSmoothing: Array[Double], topicSmoothing: Array[Double], random: MersenneTwisterFast)

Value Members

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

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

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  3. def ## (): Int

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

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

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  6. def asInstanceOf [T0] : T0

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  7. def clone (): AnyRef

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    protected[lang]
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    @throws()
  8. def decModelTopicTerm (doc: GibbsLDADocument, topic: Int, term: Int): Unit

    Decrement the given count of topic and term in the model data structures.

    Decrement the given count of topic and term in the model data structures.

    Definition Classes
    LearnSamplerHardAssignmentGibbsSampler
  9. val dist : Array[Double]

    Temporary array populated by sampling (not safe to use the same sampler in more than one thread).

    Temporary array populated by sampling (not safe to use the same sampler in more than one thread).

    Definition Classes
    Sampler
  10. def eq (arg0: AnyRef): Boolean

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  11. def equals (arg0: Any): Boolean

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  12. def finalize (): Unit

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

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  14. def hashCode (): Int

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  15. def incModelTopicTerm (doc: GibbsLDADocument, topic: Int, term: Int): Unit

    Increment the given count of topic and term in the model data structures.

    Increment the given count of topic and term in the model data structures.

    Definition Classes
    LearnSamplerHardAssignmentGibbsSampler
  16. def isInstanceOf [T0] : Boolean

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  17. def ne (arg0: AnyRef): Boolean

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  18. def notify (): Unit

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  19. def notifyAll (): Unit

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  20. val numTerms : Int

    Definition Classes
    Sampler
  21. val numTopics : Int

    Definition Classes
    Sampler
  22. def sample (doc: GibbsLDADocument): Unit

    Resamples each topic assignment in the given document.

    Resamples each topic assignment in the given document.

    Definition Classes
    HardAssignmentGibbsSampler
  23. def sampleZ (doc: GibbsLDADocument, term: Int): Int

    Creates and samples from a probability distribution over topics for a given term.

    Creates and samples from a probability distribution over topics for a given term.

    Definition Classes
    SamplerHardAssignmentGibbsSampler
  24. def synchronized [T0] (arg0: ⇒ T0): T0

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  25. val termSmoothDenom : Double

    Definition Classes
    Sampler
  26. def toString (): String

    Definition Classes
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  27. def wait (): Unit

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

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  29. def wait (arg0: Long): Unit

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Inherited from Sampler

Inherited from HardAssignmentGibbsSampler[GibbsLDADocument]

Inherited from AnyRef

Inherited from Any