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1.  final def !=(arg0: Any): Boolean

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2.  final def ##(): Int

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3.  final def ==(arg0: Any): Boolean

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4.  final def asInstanceOf[T0]: T0

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5.  def buildChild(trainingData: Seq[(Vector[AnyVal], Char, Double)], leafLearner: Learner, minLeafInstances: Int, remainingDepth: Int, maxDepth: Int, numFeatures: Int): TrainingNode[AnyVal, Char]

   Build a child node by pre-computing a split

   Build a child node by pre-computing a split

   If there isn't a split, the child is a leaf; otherwise, the child is another training node

   trainingData

   for the child

   leafLearner

   to pass through

   minLeafInstances

   minimum training instances per node

   remainingDepth

   the number of splits left

   maxDepth

   to compute depth via remainingDepth

   numFeatures

   to consider in the split

   returns

   the child node, either a RegressionTrainingNode or TrainingLeaf

6.  def clone(): AnyRef

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7.  final def eq(arg0: AnyRef): Boolean

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8.  def equals(arg0: Any): Boolean

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9.  def finalize(): Unit

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10.  final def getClass(): Class[_]

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11.  def hashCode(): Int

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12.  final def isInstanceOf[T0]: Boolean

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13.  final def ne(arg0: AnyRef): Boolean

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14.  final def notify(): Unit

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15.  final def notifyAll(): Unit

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16.  final def synchronized[T0](arg0: ⇒ T0): T0

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17.  def toString(): String

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18.  final def wait(): Unit

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

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20.  final def wait(arg0: Long): Unit

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