class Parameters extends Serializable
          
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-  new Parameters(pipe: DependencyPipe, options: Options)
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-  def assignTotal(): Unit
-  def averageParameters(T: Int, c: Float): Unit
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        clone(): AnyRef
      
      
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-  def dotProduct2L(proju: Array[Float], projv: Array[Float], projw: Array[Float], plab: Int, lab: Int, pdir: Int, dir: Int): Float
-  def dotProductL(proju: Array[Float], projv: Array[Float], lab: Int, dir: Int): Float
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-  def getDL(): Int
-  def getNumberWordFeatures(): Int
-  def getParamsL(): Array[Float]
-  def getT(): Int
-  def getU(): Array[Array[Float]]
-  def getU2(): Array[Array[Float]]
-  def getV(): Array[Array[Float]]
-  def getV2(): Array[Array[Float]]
-  def getW2(): Array[Array[Float]]
-  def getWL(): Array[Array[Float]]
-  def getX2L(): Array[Array[Float]]
-  def getY2L(): Array[Array[Float]]
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-  def printStat(): Unit
-  def projectU(fv: FeatureVector, proj: Array[Float]): Unit
-  def projectU2(fv: FeatureVector, proj: Array[Float]): Unit
-  def projectV(fv: FeatureVector, proj: Array[Float]): Unit
-  def projectV2(fv: FeatureVector, proj: Array[Float]): Unit
-  def projectW2(fv: FeatureVector, proj: Array[Float]): Unit
-  def randomlyInit(): Unit
-  def setGammaLabel(gammaLabel: Float): Unit
-  def setRankFirstOrderTensor(rankFirstOrderTensor: Int): Unit
-  def setRankSecondOrderTensor(rankSecondOrderTensor: Int): Unit
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-  def updateLabel(gold: DependencyInstance, predictedHeads: Array[Int], predictedLabels: Array[Int], localFeatureData: LocalFeatureData, updCnt: Int): Float
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