mlpack: mlpack::kmeans::PellegMooreKMeans< MetricType, MatType > Class Template Reference

mlpack master

An implementation of Pelleg-Moore's 'blacklist' algorithm for k-means clustering. More...

Public Types
typedef tree::KDTree< MetricType, PellegMooreKMeansStatistic, MatType >	TreeType
	Convenience typedef for the tree. More...

Public Member Functions
	PellegMooreKMeans (const MatType &dataset, MetricType &metric)
	Construct the PellegMooreKMeans object, which must construct a tree. More...

	~PellegMooreKMeans ()
	Delete the tree constructed by the PellegMooreKMeans object. More...

size_t	DistanceCalculations () const
	Return the number of distance calculations. More...

size_t &	DistanceCalculations ()
	Modify the number of distance calculations. More...

double	Iterate (const arma::mat &centroids, arma::mat &newCentroids, arma::Col< size_t > &counts)
	Run a single iteration of the Pelleg-Moore blacklist algorithm, updating the given centroids into the newCentroids matrix. More...

Private Attributes
const MatType &	dataset
	The dataset we are using. More...

const MatType &	datasetOrig
	The original dataset reference. More...

size_t	distanceCalculations
	Track distance calculations. More...

MetricType &	metric
	The metric. More...

TreeType *	tree
	The tree built on the points. More...

Detailed Description

template<typename MetricType, typename MatType>
class mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >

An implementation of Pelleg-Moore's 'blacklist' algorithm for k-means clustering.

This algorithm builds a kd-tree on the data points and traverses it in order to determine the closest clusters to each point.

For more information on the algorithm, see

@inproceedings{pelleg1999accelerating,
    title={Accelerating exact k-means algorithms with geometric reasoning},
    author={Pelleg, Dan and Moore, Andrew W.},
    booktitle={Proceedings of the Fifth ACM SIGKDD International Conference
      on Knowledge Discovery and Data Mining (KDD '99)},
pages={277--281},
year={1999},
organization={ACM}
}

Definition at line 42 of file pelleg_moore_kmeans.hpp.

Member Typedef Documentation

template<typename MetricType , typename MatType >

typedef tree::KDTree<MetricType, PellegMooreKMeansStatistic, MatType> mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::TreeType

Convenience typedef for the tree.

Definition at line 74 of file pelleg_moore_kmeans.hpp.

Constructor & Destructor Documentation

template<typename MetricType , typename MatType >

mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::PellegMooreKMeans	(	const MatType &	dataset,
		MetricType &	metric
	)

Construct the PellegMooreKMeans object, which must construct a tree.

template<typename MetricType , typename MatType >

mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::~PellegMooreKMeans ( )

Delete the tree constructed by the PellegMooreKMeans object.

Member Function Documentation

template<typename MetricType , typename MatType >

size_t mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::DistanceCalculations ( ) const

inline

Return the number of distance calculations.

Definition at line 68 of file pelleg_moore_kmeans.hpp.

References mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::distanceCalculations.

template<typename MetricType , typename MatType >

size_t& mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::DistanceCalculations ( )

inline

Modify the number of distance calculations.

Definition at line 70 of file pelleg_moore_kmeans.hpp.

References mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::distanceCalculations.

template<typename MetricType , typename MatType >

double mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::Iterate	(	const arma::mat &	centroids,
		arma::mat &	newCentroids,
		arma::Col< size_t > &	counts
	)

Run a single iteration of the Pelleg-Moore blacklist algorithm, updating the given centroids into the newCentroids matrix.

Parameters

centroids	Current cluster centroids.
newCentroids	New cluster centroids.
counts	Current counts, to be overwritten with new counts.

Member Data Documentation

template<typename MetricType , typename MatType >

const MatType& mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::dataset

private

The dataset we are using.

Definition at line 82 of file pelleg_moore_kmeans.hpp.

template<typename MetricType , typename MatType >

const MatType& mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::datasetOrig

private

The original dataset reference.

Definition at line 78 of file pelleg_moore_kmeans.hpp.

template<typename MetricType , typename MatType >

size_t mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::distanceCalculations

private

Track distance calculations.

Definition at line 87 of file pelleg_moore_kmeans.hpp.

Referenced by mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::DistanceCalculations().

template<typename MetricType , typename MatType >

MetricType& mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::metric

private

The metric.

Definition at line 84 of file pelleg_moore_kmeans.hpp.

template<typename MetricType , typename MatType >

TreeType* mlpack::kmeans::PellegMooreKMeans< MetricType, MatType >::tree

private

The tree built on the points.

Definition at line 80 of file pelleg_moore_kmeans.hpp.

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

src/mlpack/methods/kmeans/pelleg_moore_kmeans.hpp