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
The metric function to impose on elements of the data space
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.
The input data to sample
The desired sample size.
A sample whose expected mean size is sampleSize.
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.
The input data to sample
The desired sample size.
Seed for RNG
A sample whose expected mean size is sampleSize.
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.
The input data to sample
The desired sample size.
A sample whose expected mean size is sampleSize.
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.
The input data to sample
The desired sample size.
Seed for RNG
A sample whose expected mean size is sampleSize.
Return a given number of distinct elements randomly selected from data
Return a given number of distinct elements randomly selected from data
The data to sample from
The number of distinct samples to return
A collection of k distinct elements randomly selected from the data
If the number of distinct elements in the data is < k, an exception will be thrown
Return a given number of distinct elements randomly selected from data
Return a given number of distinct elements randomly selected from data
The data to sample from
The number of distinct samples to return
A seed to use for RNG when sampling
A collection of k distinct elements randomly selected from the data
If the number of distinct elements in the data is < k, an exception will be thrown
Return a given number of distinct elements randomly selected from data
Return a given number of distinct elements randomly selected from data
The data to sample from
The number of distinct samples to return.
Random number generator to use when sampling
A collection of k distinct elements randomly selected from the data
If the number of distinct elements in the data is < k, an exception will be thrown
Return the random sampling fraction corresponding to a desired number of samples
Return the random sampling fraction corresponding to a desired number of samples
The size of data being sampled from
The desired sample size
A sampling fraction, >= 0.0 and <= 1.0 that will yield the desired sample size
When used with typical Bernoulli sampling the returned samping fraction will yield a sample size that varies randomly, with a mean of 'sampleSize'
Utilities used by K-Medoids clustering