mlpack::kmeans::PellegMooreKMeansRules< MetricType, TreeType > Class Template Reference

The rules class for the single-tree Pelleg-Moore kd-tree traversal for k-means clustering. More...

#include <pelleg_moore_kmeans_rules.hpp>

Public Member Functions
	PellegMooreKMeansRules (const typename TreeType::Mat &dataset, const arma::mat &centroids, arma::mat &newCentroids, arma::Col< size_t > &counts, MetricType &metric)
	Create the PellegMooreKMeansRules object. More...
double	BaseCase (const size_t queryIndex, const size_t referenceIndex)
	The BaseCase() function for this single-tree algorithm does nothing. More...
double	Score (const size_t queryIndex, TreeType &referenceNode)
	Determine if a cluster can be pruned, and if not, perform point-to-cluster comparisons. More...
double	Rescore (const size_t queryIndex, TreeType &referenceNode, const double oldScore)
	Rescore to determine if a node can be pruned. More...
size_t	DistanceCalculations () const
	Get the number of distance calculations that have been performed.
size_t &	DistanceCalculations ()
	Modify the number of distance calculations that have been performed.

Detailed Description

template<typename MetricType, typename TreeType>
class mlpack::kmeans::PellegMooreKMeansRules< MetricType, TreeType >

The rules class for the single-tree Pelleg-Moore kd-tree traversal for k-means clustering.

Although TreeType is a free template parameter, this particular implementation is specialized to trees with hyper-rectangle bounds due to the pruning rule used to determine if one cluster dominates a node with respect to another cluster.

Our implementation here abuses the single-tree algorithm abstractions a little bit. Instead of doing a traversal for a particular query point, in this case we consider all clusters at once—so the query point is entirely ignored during in BaseCase() and Score().

Constructor & Destructor Documentation

PellegMooreKMeansRules()

template<typename MetricType , typename TreeType >

mlpack::kmeans::PellegMooreKMeansRules< MetricType, TreeType >::PellegMooreKMeansRules	(	const typename TreeType::Mat &	dataset,
		const arma::mat &	centroids,
		arma::mat &	newCentroids,
		arma::Col< size_t > &	counts,
		MetricType &	metric
	)

Create the PellegMooreKMeansRules object.

Parameters

dataset	The dataset that the tree is built on.
centroids	The current centroids.
newCentroids	New centroids after this iteration (output).
counts	Current cluster counts, to be replaced with new cluster counts.
metric	Instantiated metric.

Member Function Documentation

BaseCase()

template<typename MetricType , typename TreeType >

force_inline double mlpack::kmeans::PellegMooreKMeansRules< MetricType, TreeType >::BaseCase ( const size_t  queryIndex, const size_t  referenceIndex  )

inline

The BaseCase() function for this single-tree algorithm does nothing.

Instead, point-to-cluster comparisons are handled as necessary in Score().

Parameters

queryIndex	Index of query point (fake, will be ignored).
referenceIndex	Index of reference point.

Rescore()

template<typename MetricType , typename TreeType >

double mlpack::kmeans::PellegMooreKMeansRules< MetricType, TreeType >::Rescore	(	const size_t	queryIndex,
		TreeType &	referenceNode,
		const double	oldScore
	)

Rescore to determine if a node can be pruned.

In this case, a node can never be pruned during rescoring, so this just returns oldScore.

Parameters

queryIndex	Index of query point (fake, will be ignored).
referenceNode	Node containing points in the dataset.
oldScore	Resulting score from Score().

Score()

template<typename MetricType , typename TreeType >

double mlpack::kmeans::PellegMooreKMeansRules< MetricType, TreeType >::Score	(	const size_t	queryIndex,
		TreeType &	referenceNode
	)

Determine if a cluster can be pruned, and if not, perform point-to-cluster comparisons.

The point-to-cluster comparisons are performed here and not in BaseCase() because of the complexity of managing the blacklist.

Parameters

queryIndex	Index of query point (fake, will be ignored).
referenceNode	Node containing points in the dataset.

---

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

• src/mlpack/methods/kmeans/pelleg_moore_kmeans_rules.hpp
• src/mlpack/methods/kmeans/pelleg_moore_kmeans_rules_impl.hpp