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

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

#include <pelleg_moore_kmeans.hpp>

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

Public Member Functions
	PellegMooreKMeans (const MatType &dataset, MetricType &metric)
	Construct the PellegMooreKMeans object, which must construct a tree.
	~PellegMooreKMeans ()
	Delete the tree constructed by the PellegMooreKMeans object.
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...
size_t	DistanceCalculations () const
	Return the number of distance calculations.
size_t &	DistanceCalculations ()
	Modify the number of distance calculations.

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}
}

Member Function Documentation

Iterate()

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.

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

• src/mlpack/methods/kmeans/pelleg_moore_kmeans.hpp
• src/mlpack/methods/kmeans/pelleg_moore_kmeans_impl.hpp