cc.factorie.app.topics.lda

SparseLDAInferencer

class SparseLDAInferencer extends AnyRef

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Instance Constructors

  1. new SparseLDAInferencer(zDomain: variable.DiscreteDomain, wordDomain: CategoricalDomain[String], phiCounts: DiscreteMixtureCounts[String], initialAlphas: DoubleSeq, initialBeta1: Double, model: DirectedModel, random: Random, localPhiCounts: DiscreteMixtureCounts[String] = null)

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

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

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  3. final def ##(): Int

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

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def export(phis: Seq[ProportionsVar], beta1: Double = 0.0, numTopics: Int = 0): Unit

  11. def exportThetas(docs: Iterable[Doc]): Unit

  12. def finalize(): Unit

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

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  14. def hashCode(): Int

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  15. def initializeHistograms(maxDocSize: Int): Unit

  16. final def isInstanceOf[T0]: Boolean

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  17. val localPhiCounts: DiscreteMixtureCounts[String]

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

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  19. final def notify(): Unit

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  20. final def notifyAll(): Unit

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  21. val numTopics: Int

  22. var phiCounts: DiscreteMixtureCounts[String]

  23. def process(zs: DiscreteSeqVariable, timeToEstAlphas: Boolean = false): Unit

    Sample the Zs for one document.

  24. def resetCached(): Unit

  25. def resetSmoothing(newAlphas: DoubleSeq, newBeta1: Double): Unit

  26. def samplesCount: Int

  27. var smoothingMass: Double

  28. var smoothingOnlyCount: Int

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

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  30. def toString(): String

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  31. var topicBetaCount: Int

  32. def topicDocCounts: Array[Array[Int]]

  33. var topicTermCount: Int

  34. var verbosity: Int

  35. final def wait(): Unit

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

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

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  38. val wordDomain: CategoricalDomain[String]

  39. val zDomain: variable.DiscreteDomain

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