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

This is an implementation of a single iteration of Lloyd's algorithm for k-means. More...

Public Member Functions
	NaiveKMeans (const MatType &dataset, MetricType &metric)
	Construct the NaiveKMeans object with the given dataset and metric. More...
size_t	DistanceCalculations () const
double	Iterate (const arma::mat &centroids, arma::mat &newCentroids, arma::Col< size_t > &counts)
	Run a single iteration of the Lloyd algorithm, updating the given centroids into the newCentroids matrix. More...

Private Attributes
const MatType &	dataset
	The dataset. More...
size_t	distanceCalculations
	Number of distance calculations. More...
MetricType &	metric
	The instantiated metric. More...

Detailed Description

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

This is an implementation of a single iteration of Lloyd's algorithm for k-means.

If your intention is to run the full k-means algorithm, you are looking for the mlpack::kmeans::KMeans class instead of this one. This class is used by KMeans as the actual implementation of the Lloyd iteration.

Parameters

MetricType	Type of metric used with this implementation.
MatType	Matrix type (arma::mat or arma::sp_mat).

Definition at line 30 of file naive_kmeans.hpp.

Constructor & Destructor Documentation

template<typename MetricType , typename MatType >

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

Construct the NaiveKMeans object with the given dataset and metric.

Parameters

dataset	Dataset.
metric	Instantiated metric.

Member Function Documentation

template<typename MetricType , typename MatType >

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

inline

Definition at line 55 of file naive_kmeans.hpp.

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

template<typename MetricType , typename MatType >

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

Run a single iteration of the Lloyd algorithm, updating the given centroids into the newCentroids matrix.

If any cluster is empty (that is, if any cluster has no points assigned to it), then the centroid associated with that cluster may be filled with invalid data (it will be corrected later).

Parameters

centroids	Current cluster centroids.
newCentroids	New cluster centroids.
counts	Number of points in each cluster at the end of the iteration.

Member Data Documentation

template<typename MetricType , typename MatType >

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

private

The dataset.

Definition at line 59 of file naive_kmeans.hpp.

template<typename MetricType , typename MatType >

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

private

Number of distance calculations.

Definition at line 64 of file naive_kmeans.hpp.

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

template<typename MetricType , typename MatType >

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

private

The instantiated metric.

Definition at line 61 of file naive_kmeans.hpp.

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

• src/mlpack/methods/kmeans/naive_kmeans.hpp