Word2Vec

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def convertWord(str: String, lowercase: Boolean = false): String

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

final def getClass(): Class[_]

def hashCode(): Int

val hyphenPattern: Pattern

final def isInstanceOf[T0]: Boolean

def loadBansalVectorsForVocabulary(word2vecPath: String, voc: Set[String], inputVectorBias: Boolean): HashMap[String, Array[Float]]

def loadVectorsForVocabulary(word2vecPath: String, voc: Set[String], inputVectorBias: Boolean): HashMap[String, Array[Float]]

Loads vectors for a vocabulary from word2vec, with OOV words having random vectors generated for them.

def makeRandomVectorsForVocabulary(voc: Set[String], dim: Int, inputVectorBias: Boolean): HashMap[String, Array[Float]]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def readBansalEmbeddings(embeddingsPath: String, words: Set[String], inputVectorBias: Boolean): HashMap[String, Array[Float]]

def readWord2Vec(word2VecPath: String, words: Set[String], inputVectorBias: Boolean): HashMap[String, Array[Float]]

Reads the vectors in words from the given word2vec path and augments with a bias feature if necessary.

def smartLoadVectorsForVocabulary(word2vecPaths: Seq[String], voc: Set[String], vocCounts: Counter[String, Double] = Counter[String,Double], maxVectorLen: Int = Int.MaxValue, inputVectorBias: Boolean, randomizeUnks: Boolean = true): HashMap[String, Array[Float]]

Loads vectors from one or more sources in word2vecPaths; these might be in word2vec format (should end in .bin) or C+W/Bansal format (should end in .txt).

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

def toString(): String

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

final def wait(arg0: Long): Unit

final def wait(): Unit

def finalize(): Unit