Class/Object

org.clustering4ever.spark.clustering

GradientAscent

Related Docs: object GradientAscent | package clustering

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final case class GradientAscent[Hasher <: HashingScalar](k: Int, knnBucketShift: Int, epsilon: Double, maxIterations: Int, bucketLayers: Int, bucketNumber: Int, propConvStopIter: Double, memoryExpensive: Boolean, hasher: Hasher, persistanceLVL: StorageLevel = StorageLevel.MEMORY_ONLY, alternativeVectorID: Int = Int.MaxValue, fonctionalStyle: Boolean = true) extends Serializable with Product

Hasher

Gradient Ascent LSH clustering This algorithm could be used to analyse complex multivariate multidimensional data. It can also be apply in order to analyse image, to use this features it is recommanded to convert image from RGB space to L*u*v* space

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  1. GradientAscent
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Instance Constructors

  1. new GradientAscent(k: Int, knnBucketShift: Int, epsilon: Double, maxIterations: Int, bucketLayers: Int, bucketNumber: Int, propConvStopIter: Double, memoryExpensive: Boolean, hasher: Hasher, persistanceLVL: StorageLevel = StorageLevel.MEMORY_ONLY, alternativeVectorID: Int = Int.MaxValue, fonctionalStyle: Boolean = true)

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Type Members

  1. final type BucketID = Int

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Value Members

  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 val alternativeVectorID: Int

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  5. final def asInstanceOf[T0]: T0

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  6. final val bucketLayers: Int

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  7. final val bucketNumber: Int

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  8. def clone(): AnyRef

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  9. final val epsilon: Double

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

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  11. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  12. final def fit[O, Pz[B, C <: GVector[C]] <: Preprocessable[B, C, Pz]](data: RDD[Pz[O, ScalarVector]])(implicit ev: ClassTag[Pz[O, ScalarVector]]): RDD[Pz[O, ScalarVector]]

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    Gradient ascent work using LSH

  13. final val fonctionalStyle: Boolean

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

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  15. final val hasher: Hasher

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  16. final def isInstanceOf[T0]: Boolean

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  17. final val k: Int

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  18. final val knnBucketShift: Int

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  19. final val maxIterations: Int

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  20. final val memoryExpensive: Boolean

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

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  22. final def notify(): Unit

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  23. final def notifyAll(): Unit

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  24. final val persistanceLVL: StorageLevel

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  25. final val propConvStopIter: Double

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

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  27. final def wait(): Unit

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    @throws( ... )
  28. final def wait(arg0: Long, arg1: Int): Unit

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  29. final def wait(arg0: Long): Unit

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Inherited from Product

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