AbstractNBClassifier

abstract def getScoreForLabelFeature(label: Int, feature: Int): Double

scoring method for standard and complementary classifiers

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def classifyFull(r: Vector, instance: Vector): Vector

helper method for classifyFull(Vector)

def classifyFull(instance: Vector): Vector

get a scoring vector for a vector of TF of TF-IDF weights

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def getModel: NBModel

getter for model

def getScoreForLabelInstance(label: Int, instance: Vector): Double

Compute the score for a Vector of weighted TF-IDF featured

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

val model: NBModel

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def numCategories: Int

number of categories the model has been trained on

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