Object/Class

org.clustering4ever.clustering.scala.meanshift

GradientAscentScalar

Related Docs: class GradientAscentScalar | package meanshift

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object GradientAscentScalar extends Serializable

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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. final def ne(arg0: AnyRef): Boolean

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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  15. final def run[O, V <: Seq[Double], Pz[B, C <: GVector[C]] <: Preprocessable[B, C, Pz], D[X <: Seq[Double]] <: ContinuousDistance[X], KArgs <: KernelArgs, K[X <: GVector[X], Y <: KernelArgs] <: Kernel[X, Y], GS[X] <: GenSeq[X]](data: GS[Pz[O, ScalarVector[V]]], epsilon: Double, maxIterations: Int, kernel: K[ScalarVector[V], KArgs], metric: D[V], alternativeVectorID: Int = Int.MaxValue): GS[(Pz[O, ScalarVector[V]], Double)]

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    data

    GenSeq of Pz[O, ScalarVector[V]]

    epsilon

    threshold under which we stop iteration in gradient ascent

    maxIterations

    Number of iteration for modes search

  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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