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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.  def apply(x: MatrixD, k: Int, algo: Algorithm = HARTIGAN, check: Int = 3): (KMeansPPClusterer, Array[Int])

   Create a KMeansPPClusterer with random retarts.

   Create a KMeansPPClusterer with random retarts. It will restart enough times to see a local minumum 'check' times.

   x

   the vectors/points to be clustered stored as rows of a matrix

   k

   the number of clusters to make

   algo

   the clustering algorithm to use

   check

   the number of times to see local minumum before stopping

5.  final def asInstanceOf[T0]: T0

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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.  def permuteStreams(stream: Int = 0): Unit

    Create a vector that is a permutation of the current vector of random number streams.

    Create a vector that is a permutation of the current vector of random number streams.

    stream

    the stream to use in this process

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

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18.  def toString(): String

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19.  final def wait(): Unit

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

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

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