MeanShift< UseKernel, KernelType, MatType > Class Template Reference

This class implements mean shift clustering. More...

Public Member Functions
	MeanShift (const double radius=0, const size_t maxIterations=1000, const KernelType kernel=KernelType())
	Create a mean shift object and set the parameters which mean shift will be run with. More...
void	Cluster (const MatType &data, arma::Row< size_t > &assignments, arma::mat &centroids, bool forceConvergence=true, bool useSeeds=true)
	Perform mean shift clustering on the data, returning a list of cluster assignments and centroids. More...
double	EstimateRadius (const MatType &data, const double ratio=0.2)
	Give an estimation of radius based on given dataset. More...
const KernelType &	Kernel () const
	Get the kernel. More...
KernelType &	Kernel ()
	Modify the kernel. More...
size_t	MaxIterations () const
	Get the maximum number of iterations. More...
size_t &	MaxIterations ()
	Set the maximum number of iterations. More...
double	Radius () const
	Get the radius. More...
void	Radius (double radius)
	Set the radius. More...

Detailed Description

template<bool UseKernel = false, typename KernelType = kernel::GaussianKernel, typename MatType = arma::mat>
class mlpack::meanshift::MeanShift< UseKernel, KernelType, MatType >

This class implements mean shift clustering.

For each point in dataset, apply mean shift algorithm until maximum iterations or convergence. Then remove duplicate centroids.

A simple example of how to run mean shift clustering is shown below.

* extern arma::mat data; // Dataset we want to run mean shift on.
* arma::Row<size_t> assignments; // Cluster assignments.
* arma::mat centroids; // Cluster centroids.
* bool forceConvergence = true; // Flag whether to force each centroid seed
* to converge regardless of maxIterations.
*
* MeanShift<> meanShift();
* meanShift.Cluster(dataset, assignments, centroids, forceConvergence);
* 

Template Parameters

UseKernel	Use kernel or mean to calculate new centroid. If false, KernelType will be ignored.
KernelType	The kernel to use.
MatType	The type of matrix the data is stored in.

Definition at line 51 of file mean_shift.hpp.

Constructor & Destructor Documentation

MeanShift	(	const double	radius = 0,
		const size_t	maxIterations = 1000,
		const KernelType	kernel = KernelType()
	)

Create a mean shift object and set the parameters which mean shift will be run with.

Parameters

radius	If distance of two centroids is less than it, one will be removed. If this value isn't positive, an estimation will be given when clustering.
maxIterations	Maximum number of iterations allowed before giving up iterations will terminate.
kernel	Optional KernelType object.

Member Function Documentation

void Cluster	(	const MatType &	data,
		arma::Row< size_t > &	assignments,
		arma::mat &	centroids,
		bool	forceConvergence = true,
		bool	useSeeds = true
	)

Perform mean shift clustering on the data, returning a list of cluster assignments and centroids.

Template Parameters

MatType

Type of matrix.

Parameters

data	Dataset to cluster.
assignments	Vector to store cluster assignments in.
centroids	Matrix in which centroids are stored.
forceConvergence	Flag whether to force each centroid seed to converge regardless of maxIterations.

double EstimateRadius	(	const MatType &	data,
		const double	ratio = 0.2
	)

Give an estimation of radius based on given dataset.

Parameters

data	Dataset for estimation.
ratio	Percentage of dataset to use for nearest neighbor search.

const KernelType& Kernel ( ) const

inline

Get the kernel.

Definition at line 105 of file mean_shift.hpp.

KernelType& Kernel ( )

inline

Modify the kernel.

Definition at line 107 of file mean_shift.hpp.

size_t MaxIterations ( ) const

inline

Get the maximum number of iterations.

Definition at line 95 of file mean_shift.hpp.

size_t& MaxIterations ( )

inline

Set the maximum number of iterations.

Definition at line 97 of file mean_shift.hpp.

double Radius ( ) const

inline

Get the radius.

Definition at line 100 of file mean_shift.hpp.

void Radius

(

double

radius

)

Set the radius.

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

• src/mlpack/methods/mean_shift/mean_shift.hpp