com.github.cloudml.zen.ml.clustering

FastLDA

class FastLDA extends LDA

Linear Supertypes
LDA, Logging, Serializable, Serializable, AnyRef, Any
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  2. LDA
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Instance Constructors

  1. new FastLDA(docs: RDD[(DocId, Vector)], numTopics: Int, alpha: Double, beta: Double, alphaAS: Double, storageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK, computedModel: Broadcast[LocalLDAModel] = null)

  2. new FastLDA(corpus: Graph[VD, ED], numTopics: Int, numTerms: Int, alpha: Double, beta: Double, alphaAS: Double, storageLevel: StorageLevel)

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. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  10. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes
    AnyRef → Any

  12. def getCorpus: Graph[VD, ED]

    Definition Classes
    LDA

  13. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  14. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  15. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  16. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  18. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  20. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  22. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  23. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  25. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Definition Classes
    LDA

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

    Definition Classes
    AnyRef

  30. final def notify(): Unit

    Definition Classes
    AnyRef

  31. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  32. val numDocs: Long

    Doc number in corpus

    Doc number in corpus

    Definition Classes
    LDA

  33. val numTokens: Long

    Token number in corpus

    Token number in corpus

    Definition Classes
    LDA

  34. 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

  35. def runGibbsSampling(iterations: Int): Unit

    Definition Classes
    LDA

  36. def sampleTokens(graph: Graph[VD, ED], totalTopicCounter: DenseVector[Count], innerIter: Long, numTokens: Double, numTopics: Double, numTerms: Double, alpha: Double, alphaAS: Double, beta: Double): Graph[VD, ED]

    Attributes
    protected
    Definition Classes
    FastLDA → LDA

  37. def saveModel(totalIter: Int = 1): DistributedLDAModel

    Definition Classes
    LDA

  38. def setAlpha(alpha: Double): FastLDA.this.type

    Definition Classes
    LDA

  39. def setAlphaAS(alphaAS: Double): FastLDA.this.type

    Definition Classes
    LDA

  40. def setBeta(beta: Double): FastLDA.this.type

    Definition Classes
    LDA

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

    Definition Classes
    LDA

  42. def setStorageLevel(newStorageLevel: StorageLevel): FastLDA.this.type

    Definition Classes
    LDA

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

    Definition Classes
    AnyRef

  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( ... )

Inherited from LDA

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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