LDA

abstract 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]

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def getCorpus: Graph[VD, ED]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

def isTraceEnabled(): Boolean

def log: Logger

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

def logDebug(msg: ⇒ String): Unit

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

def logError(msg: ⇒ String): Unit

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

def logInfo(msg: ⇒ String): Unit

def logName: String

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

def logTrace(msg: ⇒ String): Unit

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

def logWarning(msg: ⇒ String): Unit

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

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val numDocs: Long

Doc number in corpus

val numTokens: Long

Token number in corpus

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 }}}

def runGibbsSampling(iterations: Int): Unit

def saveModel(totalIter: Int = 1): DistributedLDAModel

def setAlpha(alpha: Double): LDA.this.type

def setAlphaAS(alphaAS: Double): LDA.this.type

def setBeta(beta: Double): LDA.this.type

def setSeed(newSeed: Int): LDA.this.type

def setStorageLevel(newStorageLevel: StorageLevel): LDA.this.type

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit