com.redhat.et.silex.cluster

KMedoids

object KMedoids extends Logging with Serializable

Utilities used by K-Medoids clustering

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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  5. final def ==(arg0: Any): Boolean

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  6. def apply[T](metric: (T, T) ⇒ Double): KMedoids[T]

    Return a KMedoids object with the given metric function, and other parameters defaulted.

    Return a KMedoids object with the given metric function, and other parameters defaulted.

    Defaults are as follows:

    k = 2

    maxIterations = 25

    epsilon = 0.0

    fractionEpsilon = 0.0001

    sampleSize = 1000

    numThreads = 1

    seed = randomly initialized seed value

    metric

    The metric function to impose on elements of the data space

  7. final def asInstanceOf[T0]: T0

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  8. def clone(): AnyRef

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

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  13. def hashCode(): Int

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  15. def logDebug(msg: ⇒ String): Unit

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  16. def logError(msg: ⇒ String): Unit

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  17. def logInfo(msg: ⇒ String): Unit

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  18. def logWarning(msg: ⇒ String): Unit

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  19. def logger: Logger

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  21. final def notify(): Unit

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  22. final def notifyAll(): Unit

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  23. def sampleBySize[T](data: Seq[T], sampleSize: Int): Seq[T]

    Return a random sample of data having an expected sample size of the requested amount.

    Return a random sample of data having an expected sample size of the requested amount.

    data

    The input data to sample

    sampleSize

    The desired sample size.

    returns

    A sample whose expected mean size is sampleSize.

  24. def sampleBySize[T](data: Seq[T], sampleSize: Int, seed: Long): Seq[T]

    Return a random sample of data having an expected sample size of the requested amount.

    Return a random sample of data having an expected sample size of the requested amount.

    data

    The input data to sample

    sampleSize

    The desired sample size.

    seed

    Seed for RNG

    returns

    A sample whose expected mean size is sampleSize.

  25. def sampleBySize[T](data: RDD[T], sampleSize: Int): Seq[T]

    Return a random sample of data having an expected sample size of the requested amount.

    Return a random sample of data having an expected sample size of the requested amount.

    data

    The input data to sample

    sampleSize

    The desired sample size.

    returns

    A sample whose expected mean size is sampleSize.

  26. def sampleBySize[T](data: RDD[T], sampleSize: Int, seed: Long): Seq[T]

    Return a random sample of data having an expected sample size of the requested amount.

    Return a random sample of data having an expected sample size of the requested amount.

    data

    The input data to sample

    sampleSize

    The desired sample size.

    seed

    Seed for RNG

    returns

    A sample whose expected mean size is sampleSize.

  27. def sampleDistinct[T](data: Seq[T], k: Int): Seq[T]

    Return a given number of distinct elements randomly selected from data

    Return a given number of distinct elements randomly selected from data

    data

    The data to sample from

    k

    The number of distinct samples to return

    returns

    A collection of k distinct elements randomly selected from the data

    Note

    If the number of distinct elements in the data is < k, an exception will be thrown

  28. def sampleDistinct[T](data: Seq[T], k: Int, seed: Long): Seq[T]

    Return a given number of distinct elements randomly selected from data

    Return a given number of distinct elements randomly selected from data

    data

    The data to sample from

    k

    The number of distinct samples to return

    seed

    A seed to use for RNG when sampling

    returns

    A collection of k distinct elements randomly selected from the data

    Note

    If the number of distinct elements in the data is < k, an exception will be thrown

  29. def sampleDistinct[T](data: Seq[T], k: Int, rng: Random): Seq[T]

    Return a given number of distinct elements randomly selected from data

    Return a given number of distinct elements randomly selected from data

    data

    The data to sample from

    k

    The number of distinct samples to return.

    rng

    Random number generator to use when sampling

    returns

    A collection of k distinct elements randomly selected from the data

    Note

    If the number of distinct elements in the data is < k, an exception will be thrown

  30. def sampleFraction[N](n: N, sampleSize: Int)(implicit arg0: Numeric[N]): Double

    Return the random sampling fraction corresponding to a desired number of samples

    Return the random sampling fraction corresponding to a desired number of samples

    n

    The size of data being sampled from

    sampleSize

    The desired sample size

    returns

    A sampling fraction, >= 0.0 and <= 1.0 that will yield the desired sample size

    Note

    When used with typical Bernoulli sampling the returned samping fraction will yield a sample size that varies randomly, with a mean of 'sampleSize'

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

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  32. def toString(): String

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  33. final def wait(): Unit

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

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

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