PLDAModelParams

def != (arg0: AnyRef): Boolean

def != (arg0: Any): Boolean

def ## (): Int

def == (arg0: AnyRef): Boolean

def == (arg0: Any): Boolean

def asInstanceOf [T0] : T0

def canEqual (arg0: Any): Boolean

def clone (): AnyRef

def eq (arg0: AnyRef): Boolean

def equals (arg0: Any): Boolean

def finalize (): Unit

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

def hashCode (): Int

def isInstanceOf [T0] : Boolean

val labelIndex : Option[Index[String]]

Names for each label

def ne (arg0: AnyRef): Boolean

def notify (): Unit

def notifyAll (): Unit

def numLabels : Int

val numLatentTopics : Int

Number of latent topics applied to each document.

val numTerms : Int

Total number of terms in the model.

def numTopics : Int

val numTopicsPerLabel : Array[Int]

For each label, how many topics.

def productArity : Int

def productElement (arg0: Int): Any

def productIterator : Iterator[Any]

def productPrefix : String

def signature : String

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

val termIndex : Option[Index[String]]

Names for each term

val termSmoothing : DirichletParams

per-term Dirichlet smoothing

def toString (): String

val tokenizer : Option[Tokenizer]

Tokenizer used during construction

val topicIndex : Option[Index[String]]

Names for each topic (with numTopicsPerLabel for each label)

val topicSmoothing : DirichletParams

per-topic Dirichlet smoothing

def wait (): Unit

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

def wait (arg0: Long): Unit

def productElements : Iterator[Any]