edu.stanford.nlp.tmt.model

HardAssignmentGibbsSampler

class HardAssignmentGibbsSampler [Document <: HardAssignmentDocument] extends AnyRef

Abstract base class of a Gibbs sampler for LDA. Not threadsafe.

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  1. HardAssignmentGibbsSampler
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Instance Constructors

  1. new HardAssignmentGibbsSampler ()

Abstract Value Members

  1. def decModelTopicTerm (doc: Document, 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.

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  2. def incModelTopicTerm (doc: Document, 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.

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  3. def sampleZ (doc: Document, 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.

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  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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  6. def asInstanceOf [T0] : T0

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  7. def clone (): AnyRef

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  10. def finalize (): Unit

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

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  12. def hashCode (): Int

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  14. def ne (arg0: AnyRef): Boolean

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  15. def notify (): Unit

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  16. def notifyAll (): Unit

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  17. def sample (doc: Document): Unit

    Resamples each topic assignment in the given document.

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

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  19. def toString (): String

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  20. def wait (): Unit

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

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  22. def wait (arg0: Long): Unit

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