FastLDA

Value Members

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

   Definition Classes

   AnyRef

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

   Definition Classes

   Any

3. final def ##(): Int

   Definition Classes

   AnyRef → Any

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

   Definition Classes

   AnyRef

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

   Definition Classes

   Any

6. final def asInstanceOf[T0]: T0

   Definition Classes

   Any

7. def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

8. def docVertices: VertexRDD[VD]

   Definition Classes

   LDA

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

   Definition Classes

   AnyRef

10. def equals(arg0: Any): Boolean

    Definition Classes

    AnyRef → Any

11. def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes

    AnyRef → Any

13. def getCorpus: Graph[VD, ED]

    Definition Classes

    LDA

14. def hashCode(): Int

    Definition Classes

    AnyRef → Any

15. final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

16. def isTraceEnabled(): Boolean

    Attributes

    protected

    Definition Classes

    Logging

17. def log: Logger

    Attributes

    protected

    Definition Classes

    Logging

18. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes

    protected

    Definition Classes

    Logging

19. def logDebug(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

20. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes

    protected

    Definition Classes

    Logging

21. def logError(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

22. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes

    protected

    Definition Classes

    Logging

23. def logInfo(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

24. def logName: String

    Attributes

    protected

    Definition Classes

    Logging

25. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes

    protected

    Definition Classes

    Logging

26. def logTrace(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

27. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes

    protected

    Definition Classes

    Logging

28. def logWarning(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

29. def mergeDuplicateTopic(threshold: Double = 0.95D): Map[Int, Int]

    Definition Classes

    LDA

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

    Definition Classes

    AnyRef

31. final def notify(): Unit

    Definition Classes

    AnyRef

32. final def notifyAll(): Unit

    Definition Classes

    AnyRef

33. def perplexity(): Double

    the multiplcation between word distribution among all topics and the corresponding doc distribution among all topics: p(w)=\sum_{k}{p(k|d)*p(w|k)}= \sum_{k}{\frac{{n}_{kw}+{\beta }_{w}} {{n}_{k}+\bar{\beta }} \frac{{n}_{kd}+{\alpha }_{k}}{\sum{{n}_{k}}+ \bar{\alpha }}}

    the multiplcation between word distribution among all topics and the corresponding doc distribution among all topics: p(w)=\sum_{k}{p(k|d)*p(w|k)}= \sum_{k}{\frac{{n}_{kw}+{\beta }_{w}} {{n}_{k}+\bar{\beta }} \frac{{n}_{kd}+{\alpha }_{k}}{\sum{{n}_{k}}+ \bar{\alpha }}}

    \sum_{k} \frac{{\alpha }_{k}{\beta }_{w} + {n}_{kw}{\alpha }_{k} + {n}_{kd}{\beta }_{w} + {n}_{kw}{n}_{kd}} {{n}_{k}+\bar{\beta }} \frac{1}{\sum{{n}_{k}}+\bar{\alpha }}} \exp^{-(\sum{\log(p(w))})/N} N is the number of tokens in corpus

    \bar{\alpha }}} \sum_{k} \frac{{\alpha }_{k}{\beta }_{w} + {n}_{kw}{\alpha }_{k} + {n}_{kd}{\beta }_{w} + {n}_{kw}{n}_{kd}} {{n}_{k}+\bar{\beta }} \frac{1}{\sum{{n}_{k}}+\bar{\alpha }}} \exp^{-(\sum{\log(p(w))})/N} N is the number of tokens in corpus

    Definition Classes

    LDA

34. def runGibbsSampling(totalIter: Int, ChkptInterval: Int = 0, calcPerplexity: Boolean = false): Unit

    Definition Classes

    LDA

35. def sampleTokens(corpus: Graph[VD, ED], totalTopicCounter: DenseVector[Count], pseudoIter: Int, numTokens: Long, numTopics: Int, numTerms: Int, alpha: Float, alphaAS: Float, beta: Float): Graph[VD, ED]

    Attributes

    protected

    Definition Classes

    FastLDA → LDA

36. def saveModel(saveIter: Int = 1): DistributedLDAModel

    Save the term-topic related model

    Save the term-topic related model

    saveIter

    saved these iters' averaged model

    Definition Classes

    LDA

37. def setAlpha(alpha: Float): FastLDA.this.type

    Definition Classes

    LDA

38. def setAlphaAS(alphaAS: Float): FastLDA.this.type

    Definition Classes

    LDA

39. def setBeta(beta: Float): FastLDA.this.type

    Definition Classes

    LDA

40. def setSeed(newSeed: Int): FastLDA.this.type

    Definition Classes

    LDA

41. def setStorageLevel(storageLevel: StorageLevel): FastLDA.this.type

    Definition Classes

    LDA

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

    Definition Classes

    AnyRef

43. def termVertices: VertexRDD[VD]

    Definition Classes

    LDA

44. def toString(): String

    Definition Classes

    AnyRef → Any

45. final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )