Gaussian Mixture Models - Implementation. More...

#include "gmm.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "mathop_avx.h"
#include "shuffle-def.h"

Functions
VlGMM *	vl_gmm_new (vl_type dataType, vl_size dimension, vl_size numComponents)
	Create a new GMM object. More...

void	vl_gmm_reset (VlGMM *self)
	Reset state. More...

void	vl_gmm_delete (VlGMM *self)
	Deletes a GMM object. More...

vl_type	vl_gmm_get_data_type (VlGMM const *self)
	Get data type. More...

vl_size	vl_gmm_get_num_clusters (VlGMM const *self)
	Get the number of clusters. More...

vl_size	vl_gmm_get_num_data (VlGMM const *self)
	Get the number of data points. More...

double	vl_gmm_get_loglikelihood (VlGMM const *self)
	Get the log likelihood of the current mixture. More...

int	vl_gmm_get_verbosity (VlGMM const *self)
	Get verbosity level. More...

void	vl_gmm_set_verbosity (VlGMM *self, int verbosity)
	Set verbosity level. More...

void const *	vl_gmm_get_means (VlGMM const *self)
	Get means. More...

void const *	vl_gmm_get_covariances (VlGMM const *self)
	Get covariances. More...

void const *	vl_gmm_get_priors (VlGMM const *self)
	Get priors. More...

void const *	vl_gmm_get_posteriors (VlGMM const *self)
	Get posteriors. More...

vl_size	vl_gmm_get_max_num_iterations (VlGMM const *self)
	Get maximum number of iterations. More...

void	vl_gmm_set_max_num_iterations (VlGMM *self, vl_size maxNumIterations)
	Set maximum number of iterations. More...

void	vl_gmm_set_num_repetitions (VlGMM *self, vl_size numRepetitions)
	Set maximum number of repetitions. More...

vl_size	vl_gmm_get_dimension (VlGMM const *self)
	Get data dimension. More...

VlGMMInitialization	vl_gmm_get_initialization (VlGMM const *self)
	Get initialization algorithm. More...

void	vl_gmm_set_initialization (VlGMM *self, VlGMMInitialization init)
	Set initialization algorithm. More...

VlKMeans *	vl_gmm_get_kmeans_init_object (VlGMM const *self)
	Get KMeans initialization object. More...

void	vl_gmm_set_kmeans_init_object (VlGMM self, VlKMeans kmeans)
	Set KMeans initialization object. More...

double const *	vl_gmm_get_covariance_lower_bounds (VlGMM const *self)
	Get the lower bound on the diagonal covariance values. More...

void	vl_gmm_set_covariance_lower_bounds (VlGMM self, double const bounds)
	Set the lower bounds on diagonal covariance values. More...

void	vl_gmm_set_covariance_lower_bound (VlGMM *self, double bound)
	Set the lower bounds on diagonal covariance values. More...

VlGMM *	vl_gmm_new_copy (VlGMM const *self)
	Create a new GMM object by copy. More...

void	vl_gmm_init_with_rand_data (VlGMM self, void const data, vl_size numData)
	Initialize mixture before EM takes place using random initialization. More...

void	vl_gmm_init_with_kmeans (VlGMM self, void const data, vl_size numData, VlKMeans *kmeansInit)
	Initializes the GMM using KMeans. More...

double	vl_gmm_cluster (VlGMM self, void const data, vl_size numData)
	Run GMM clustering - includes initialization and EM. More...

double	vl_gmm_em (VlGMM self, void const data, vl_size numData)
	Invoke the EM algorithm. More...

void	vl_gmm_set_means (VlGMM self, void const means)
	Explicitly set the initial means for EM. More...

void	vl_gmm_set_covariances (VlGMM self, void const covariances)
	Explicitly set the initial sigma diagonals for EM. More...

void	vl_gmm_set_priors (VlGMM self, void const priors)
	Explicitly set the initial priors of the gaussians. More...

Get parameters
vl_size	vl_gmm_get_num_repetitions (VlGMM const *self)
	Get maximum number of repetitions. More...

Detailed Description

Author: David Novotny; Andrea Vedaldi

Function Documentation

◆ vl_gmm_cluster()

double vl_gmm_cluster	(	VlGMM *	self,
		void const *	data,
		vl_size	numData
	)

Parameters

self	GMM object instance.
data	data points which should be clustered.
numData	number of data points.

◆ vl_gmm_delete()

void vl_gmm_delete ( VlGMM * self )

Parameters

self	GMM object instance.

The function deletes the GMM object instance created by vl_gmm_new.

◆ vl_gmm_em()

double vl_gmm_em	(	VlGMM *	self,
		void const *	data,
		vl_size	numData
	)

Parameters

self	GMM object instance.
data	data points which should be clustered.
numData	number of data points.

◆ vl_gmm_get_covariance_lower_bounds()

double const* vl_gmm_get_covariance_lower_bounds ( VlGMM const * self )

Parameters

self object

Returns: lower bound on covariances.

◆ vl_gmm_get_covariances()

void const* vl_gmm_get_covariances ( VlGMM const * self )

Parameters

self object

Returns: diagonals of cluster covariance matrices.

◆ vl_gmm_get_data_type()

vl_type vl_gmm_get_data_type ( VlGMM const * self )

Parameters

self object

Returns: data type.

◆ vl_gmm_get_dimension()

vl_size vl_gmm_get_dimension ( VlGMM const * self )

Parameters

self object

Returns: data dimension.

◆ vl_gmm_get_initialization()

VlGMMInitialization vl_gmm_get_initialization ( VlGMM const * self )

Parameters

self object

Returns: initialization algorithm.

◆ vl_gmm_get_kmeans_init_object()

VlKMeans* vl_gmm_get_kmeans_init_object ( VlGMM const * self )

Parameters

self object

Returns: kmeans initialization object.

◆ vl_gmm_get_loglikelihood()

double vl_gmm_get_loglikelihood ( VlGMM const * self )

Parameters

self object

Returns: loglikelihood.

◆ vl_gmm_get_max_num_iterations()

vl_size vl_gmm_get_max_num_iterations ( VlGMM const * self )

Parameters

self object

Returns: maximum number of iterations.

◆ vl_gmm_get_means()

void const* vl_gmm_get_means ( VlGMM const * self )

Parameters

self object

Returns: cluster means.

◆ vl_gmm_get_num_clusters()

vl_size vl_gmm_get_num_clusters ( VlGMM const * self )

Parameters

self object

Returns: number of clusters.

◆ vl_gmm_get_num_data()

vl_size vl_gmm_get_num_data ( VlGMM const * self )

Parameters

self object

Returns: number of data points.

◆ vl_gmm_get_num_repetitions()

vl_size vl_gmm_get_num_repetitions ( VlGMM const * self )

Parameters

self object

Returns: current number of repretitions for quantization.

◆ vl_gmm_get_posteriors()

void const* vl_gmm_get_posteriors ( VlGMM const * self )

Parameters

self object

Returns: posterior probabilities of cluster memberships.

◆ vl_gmm_get_priors()

void const* vl_gmm_get_priors ( VlGMM const * self )

Parameters

self object

Returns: priors of cluster gaussians.

◆ vl_gmm_get_verbosity()

int vl_gmm_get_verbosity ( VlGMM const * self )

Parameters

self object

Returns: verbosity level.

◆ vl_gmm_init_with_kmeans()

void vl_gmm_init_with_kmeans	(	VlGMM *	self,
		void const *	data,
		vl_size	numData,
		VlKMeans *	kmeansInit
	)

Parameters

self	GMM object instance.
data	data points which should be clustered.
numData	number of data points.
kmeansInit	KMeans object to use.

◆ vl_gmm_init_with_rand_data()

void vl_gmm_init_with_rand_data	(	VlGMM *	self,
		void const *	data,
		vl_size	numData
	)

Parameters

self	GMM object instance.
data	data points which should be clustered.
numData	number of data points.

◆ vl_gmm_new()

VlGMM* vl_gmm_new	(	vl_type	dataType,
		vl_size	dimension,
		vl_size	numComponents
	)

Parameters

dataType	type of data (VL_TYPE_FLOAT or VL_TYPE_DOUBLE)
dimension	dimension of the data.
numComponents	number of Gaussian mixture components.

Returns: new GMM object instance.

◆ vl_gmm_new_copy()

VlGMM* vl_gmm_new_copy ( VlGMM const * self )

Parameters

self object.

Returns: new copy.

Most parameters, including the cluster priors, means, and covariances are copied. Data posteriors (available after initalization or EM) are not; nor is the KMeans object used for initialization, if any.

◆ vl_gmm_reset()

void vl_gmm_reset ( VlGMM * self )

Parameters

self object.

The function reset the state of the GMM object. It deletes any stored posterior and other internal state variables.

◆ vl_gmm_set_covariance_lower_bound()

void vl_gmm_set_covariance_lower_bound	(	VlGMM *	self,
		double	bound
	)

Parameters

self	object.
bound	bound.

While there is one lower bound per dimension, this function sets all of them to the specified scalar. Use vl_gmm_set_covariance_lower_bounds to set them individually.

◆ vl_gmm_set_covariance_lower_bounds()

void vl_gmm_set_covariance_lower_bounds	(	VlGMM *	self,
		double const *	bounds
	)

Parameters

self	object.
bounds	bounds.

There is one lower bound per dimension. Use vl_gmm_set_covariance_lower_bound to set all of them to a given scalar.

◆ vl_gmm_set_covariances()

void vl_gmm_set_covariances	(	VlGMM *	self,
		void const *	covariances
	)

Parameters

self	GMM object instance.
covariances	initial values of covariance matrix diagonals.

◆ vl_gmm_set_initialization()

void vl_gmm_set_initialization	(	VlGMM *	self,
		VlGMMInitialization	init
	)

Parameters

self	object
init	initialization algorithm.

◆ vl_gmm_set_kmeans_init_object()

void vl_gmm_set_kmeans_init_object	(	VlGMM *	self,
		VlKMeans *	kmeans
	)

Parameters

self	object
kmeans	initialization KMeans object.

◆ vl_gmm_set_max_num_iterations()

void vl_gmm_set_max_num_iterations	(	VlGMM *	self,
		vl_size	maxNumIterations
	)

Parameters

self	VlGMM filter.
maxNumIterations	maximum number of iterations.

◆ vl_gmm_set_means()

void vl_gmm_set_means	(	VlGMM *	self,
		void const *	means
	)

Parameters

self	GMM object instance.
means	initial values of means.

◆ vl_gmm_set_num_repetitions()

void vl_gmm_set_num_repetitions	(	VlGMM *	self,
		vl_size	numRepetitions
	)

Parameters

self	object
numRepetitions	maximum number of repetitions. The number of repetitions cannot be smaller than 1.

◆ vl_gmm_set_priors()

void vl_gmm_set_priors	(	VlGMM *	self,
		void const *	priors
	)

Parameters

self	GMM object instance.
priors	initial values of the gaussian priors.

◆ vl_gmm_set_verbosity()

void vl_gmm_set_verbosity	(	VlGMM *	self,
		int	verbosity
	)

Parameters

self	object
verbosity	verbosity level.

VLFeat.org

Functions

Detailed Description

Function Documentation

◆ vl_gmm_cluster()

◆ vl_gmm_delete()

◆ vl_gmm_em()

◆ vl_gmm_get_covariance_lower_bounds()

◆ vl_gmm_get_covariances()

◆ vl_gmm_get_data_type()

◆ vl_gmm_get_dimension()

◆ vl_gmm_get_initialization()

◆ vl_gmm_get_kmeans_init_object()

◆ vl_gmm_get_loglikelihood()

◆ vl_gmm_get_max_num_iterations()

◆ vl_gmm_get_means()

◆ vl_gmm_get_num_clusters()

◆ vl_gmm_get_num_data()

◆ vl_gmm_get_num_repetitions()

◆ vl_gmm_get_posteriors()

◆ vl_gmm_get_priors()

◆ vl_gmm_get_verbosity()

◆ vl_gmm_init_with_kmeans()

◆ vl_gmm_init_with_rand_data()

◆ vl_gmm_new()

◆ vl_gmm_new_copy()

◆ vl_gmm_reset()

◆ vl_gmm_set_covariance_lower_bound()

◆ vl_gmm_set_covariance_lower_bounds()

◆ vl_gmm_set_covariances()

◆ vl_gmm_set_initialization()

◆ vl_gmm_set_kmeans_init_object()

◆ vl_gmm_set_max_num_iterations()

◆ vl_gmm_set_means()

◆ vl_gmm_set_num_repetitions()

◆ vl_gmm_set_priors()

◆ vl_gmm_set_verbosity()