KMedoids

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
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
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def logDebug(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logger: Logger

Definition Classes
Logging
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
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.
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.
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.
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.
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
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
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
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'
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Docs: class KMedoids | package cluster

object KMedoids extends Logging with Serializable

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

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

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String): Unit

def logWarning(msg: ⇒ String): Unit

def logger: Logger

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

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

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

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

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

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

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

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

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Logging

Inherited from AnyRef

Inherited from Any

Ungrouped