FastCoreset Class Reference

Fast implementation of PROBI. More...

#include <FastCoreset.hpp>

Public Member Functions
	FastCoreset (std::function< Metric< Point > *() > createMetric, std::function< Norm< Point > *() > createNorm)
void	setK (int k)
	Sets number of centers. More...
int	getK () const
	Gets number of centers. More...
void	setWeiszfeldMedianIterations (int weiszfeldMedianIterations)
	Sets number of Weiszfeld iterations (approximation of 1-median) More...
int	getWeiszfeldMedianIterations () const
	Gets number of Weiszfeld iterations (approximation of 1-median) More...
void	setMaxLloydClusteringIterations (int maxLloydClusteringIterations)
	Sets number of "probabilistic Lloyd" iterations. More...
int	getMaxLloydClusteringIterations () const
	Gets number of "probabilistic Lloyd" iterations. More...
void	setKumarMedianIterations (int kumarMedianIterations)
	Sets number of iterations in Kumar's k-median algorithm (fallback) More...
int	getKumarMedianIterations () const
	Gets number of iterations in Kumar's k-median algorithm (fallback) More...
void	setAllSamplesSize (int allSamplesSize)
	Sets the ring sample size. More...
int	getAllSamplesSize () const
	Gets the ring sample size. More...
template<typename Iterator1 , typename Iterator2 >
void	computeCoreset (Iterator1 inputBegin, Iterator1 inputEnd, Iterator2 output, size_t n=0)
template<typename RandomAccessIterator1 , typename Iterator2 >
void	computeCoreset (RandomAccessIterator1 inputBegin, RandomAccessIterator1 inputEnd, Iterator2 output, size_t n)

Detailed Description

Fast implementation of PROBI.

PROBI is a clustering algorithm for the probabilistic Euclidean k-median problem.

Member Function Documentation

template<typename Iterator1 , typename Iterator2 >

void FastCoreset::computeCoreset	(	Iterator1	inputBegin,
		Iterator1	inputEnd,
		Iterator2	output,
		size_t	n = 0
	)

Computes a k-median coreset

Parameters

begin	Input point set: begin
end	Input point set: end
output	Output iterator
n	Size of input (optional)

Returns

k-median coreset

int FastCoreset::getAllSamplesSize

(

)

const

Gets the ring sample size.

Returns

Ring sample size

int FastCoreset::getK

(

)

const

Gets number of centers.

Returns

Number of centers

int FastCoreset::getKumarMedianIterations

(

)

const

Gets number of iterations in Kumar's k-median algorithm (fallback)

Returns

Maximum number of iterations

int FastCoreset::getMaxLloydClusteringIterations

(

)

const

Gets number of "probabilistic Lloyd" iterations.

Returns

Maximum number of iterations

int FastCoreset::getWeiszfeldMedianIterations

(

)

const

Gets number of Weiszfeld iterations (approximation of 1-median)

Returns

Maximum number of iterations

void FastCoreset::setAllSamplesSize

(

int

allSamplesSize)

Sets the ring sample size.

Parameters

allSamplesSize

Ring sample size

void FastCoreset::setK

(

int

k)

Sets number of centers.

Parameters

k	Number of centers

void FastCoreset::setKumarMedianIterations

(

int

kumarMedianIterations)

Sets number of iterations in Kumar's k-median algorithm (fallback)

Parameters

kumarMedianIterations

Maximum number of iterations

void FastCoreset::setMaxLloydClusteringIterations

(

int

maxLloydClusteringIterations)

Sets number of "probabilistic Lloyd" iterations.

Parameters

maxLloydClusteringIterations

Maximum number of iterations

void FastCoreset::setWeiszfeldMedianIterations

(

int

weiszfeldMedianIterations)

Sets number of Weiszfeld iterations (approximation of 1-median)

Parameters

weiszfeldMedianIterations

Maximum number of iterations

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The documentation for this class was generated from the following files:

• FastCoreset.hpp
• FastCoreset.cpp