itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample > Class Template Reference

This class generates the parameter estimates for a mixture model using expectation maximization strategy. More...

#include <itkExpectationMaximizationMixtureModelEstimator.h>

Inheritance diagram for itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >:

Collaboration diagram for itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >:

List of all members.

Public Types
typedef MembershipFunctionBase < MeasurementVectorType >	ComponentMembershipFunctionType
typedef MixtureModelComponentBase < TSample >	ComponentType
typedef std::vector < ComponentType * >	ComponentVectorType
typedef SmartPointer< const Self >	ConstPointer
typedef GaussianMembershipFunctionType::Pointer	GaussianMembershipFunctionPointer
typedef GaussianMembershipFunction < MeasurementVectorType >	GaussianMembershipFunctionType
typedef TSample::MeasurementType	MeasurementType
typedef TSample::MeasurementVectorType	MeasurementVectorType
typedef MembershipFunctionType::ConstPointer	MembershipFunctionPointer
typedef SimpleDataObjectDecorator < ProportionVectorType >	MembershipFunctionsWeightsArrayObjectType
typedef MembershipFunctionsWeightsArrayObjectType::Pointer	MembershipFunctionsWeightsArrayPointer
typedef MembershipFunctionBase < MeasurementVectorType >	MembershipFunctionType
typedef MembershipFunctionVectorObjectType::Pointer	MembershipFunctionVectorObjectPointer
typedef SimpleDataObjectDecorator < MembershipFunctionVectorType >	MembershipFunctionVectorObjectType
typedef std::vector < MembershipFunctionPointer >	MembershipFunctionVectorType
typedef SmartPointer< Self >	Pointer
typedef Array< double >	ProportionVectorType
typedef TSample	SampleType
typedef ExpectationMaximizationMixtureModelEstimator	Self
typedef Object	Superclass
enum	TERMINATION_CODE {   CONVERGED = 0,   NOT_CONVERGED = 1 }
Public Member Functions
int	AddComponent (ComponentType *component)
ComponentMembershipFunctionType *	GetComponentMembershipFunction (int componentIndex) const
int	GetCurrentIteration ()
const ProportionVectorType &	GetInitialProportions () const
int	GetMaximumIteration () const
const MembershipFunctionsWeightsArrayObjectType *	GetMembershipFunctionsWeightsArray () const
unsigned int	GetNumberOfComponents () const
const MembershipFunctionVectorObjectType *	GetOutput () const
const ProportionVectorType &	GetProportions () const
const TSample *	GetSample () const
TERMINATION_CODE	GetTerminationCode () const
void	SetInitialProportions (ProportionVectorType &propotion)
void	SetMaximumIteration (int numberOfIterations)
void	SetSample (const TSample *sample)
void	Update ()
Protected Member Functions
bool	CalculateDensities ()
double	CalculateExpectation () const
	ExpectationMaximizationMixtureModelEstimator ()
void	GenerateData ()
void	PrintSelf (std::ostream &os, Indent indent) const
bool	UpdateComponentParameters ()
bool	UpdateProportions ()
virtual	~ExpectationMaximizationMixtureModelEstimator ()
Private Attributes
ComponentVectorType	m_ComponentVector
int	m_CurrentIteration
ProportionVectorType	m_InitialProportions
int	m_MaxIteration
MembershipFunctionVectorObjectPointer	m_MembershipFunctionsObject
MembershipFunctionsWeightsArrayPointer	m_MembershipFunctionsWeightArrayObject
ProportionVectorType	m_Proportions
const TSample *	m_Sample
TERMINATION_CODE	m_TerminationCode
virtual const char *	GetNameOfClass () const
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
static Pointer	New ()

---

Detailed Description

template<class TSample>
class itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >

This class generates the parameter estimates for a mixture model using expectation maximization strategy.

The first template argument is the type of the target sample data. This estimator expects one or more mixture model component objects of the classes derived from the MixtureModelComponentBase. The actual component (or module) parameters are updated by each component. Users can think this class as a strategy or a integration point for the EM procedure. The initial proportion (SetInitialProportions), the input sample (SetSample), the mixture model components (AddComponent), and the maximum iteration (SetMaximumIteration) are required. The EM procedure terminates when the current iteration reaches the maximum iteration or the model parameters converge.

Recent API changes: The static const macro to get the length of a measurement vector, MeasurementVectorSize has been removed to allow the length of a measurement vector to be specified at run time. It is now obtained at run time from the sample set as input. Please use the function GetMeasurementVectorSize() to get the length.

See also:

MixtureModelComponentBase, GaussianMixtureModelComponent

Wiki Examples:

• All Examples

• 2D Gaussian Mixture Model Expectation Maximization

Definition at line 61 of file itkExpectationMaximizationMixtureModelEstimator.h.

---

Member Typedef Documentation

template<class TSample >

typedef MembershipFunctionBase< MeasurementVectorType > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::ComponentMembershipFunctionType

Type of the membership function base class

Definition at line 105 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef MixtureModelComponentBase< TSample > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::ComponentType

Type of the mixture model component base class

Definition at line 98 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef std::vector< ComponentType * > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::ComponentVectorType

Type of the component pointer storage

Definition at line 101 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef SmartPointer< const Self > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::ConstPointer

Reimplemented from itk::Object.

Definition at line 68 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef GaussianMembershipFunctionType::Pointer itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GaussianMembershipFunctionPointer

Definition at line 87 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef GaussianMembershipFunction< MeasurementVectorType > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GaussianMembershipFunctionType

Typedef requried to generate dataobject decorated output that can be plugged into SampleClassifierFilter

Definition at line 84 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef TSample::MeasurementType itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MeasurementType

Definition at line 78 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef TSample::MeasurementVectorType itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MeasurementVectorType

Definition at line 79 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef MembershipFunctionType::ConstPointer itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MembershipFunctionPointer

Definition at line 90 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef SimpleDataObjectDecorator< ProportionVectorType > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MembershipFunctionsWeightsArrayObjectType

typedef for decorated array of proportion

Definition at line 127 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef MembershipFunctionsWeightsArrayObjectType::Pointer itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MembershipFunctionsWeightsArrayPointer

Definition at line 129 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef MembershipFunctionBase< MeasurementVectorType > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MembershipFunctionType

Definition at line 89 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef MembershipFunctionVectorObjectType::Pointer itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MembershipFunctionVectorObjectPointer

Definition at line 95 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef SimpleDataObjectDecorator< MembershipFunctionVectorType > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MembershipFunctionVectorObjectType

Definition at line 93 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef std::vector< MembershipFunctionPointer > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::MembershipFunctionVectorType

Definition at line 91 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef SmartPointer< Self > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::Pointer

Reimplemented from itk::Object.

Definition at line 67 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef Array< double > itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::ProportionVectorType

Type of the array of the proportion values

Definition at line 108 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef TSample itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::SampleType

TSample template argument related typedefs

Definition at line 73 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef ExpectationMaximizationMixtureModelEstimator itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::Self

Standard class typedef

Reimplemented from itk::Object.

Definition at line 65 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

typedef Object itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::Superclass

Reimplemented from itk::Object.

Definition at line 66 of file itkExpectationMaximizationMixtureModelEstimator.h.

---

Member Enumeration Documentation

template<class TSample >

enum itk::Statistics::ExpectationMaximizationMixtureModelEstimator::TERMINATION_CODE

Termination status after running optimization

Enumerator:

CONVERGED
NOT_CONVERGED

Definition at line 158 of file itkExpectationMaximizationMixtureModelEstimator.h.

---

Constructor & Destructor Documentation

template<class TSample >

itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::ExpectationMaximizationMixtureModelEstimator

(

)

[protected]

template<class TSample >

virtual itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::~ExpectationMaximizationMixtureModelEstimator

(

)

[inline, protected, virtual]

Definition at line 173 of file itkExpectationMaximizationMixtureModelEstimator.h.

---

Member Function Documentation

template<class TSample >

int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::AddComponent

(

ComponentType *

component

)

Adds a new component (or class).

template<class TSample >

bool itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::CalculateDensities

(

)

[protected]

template<class TSample >

double itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::CalculateExpectation

(

)

const [protected]

template<class TSample >

virtual::itk::LightObject::Pointer itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::CreateAnother

(

void

)

const [virtual]

Standard macros

Reimplemented from itk::Object.

template<class TSample >

void itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GenerateData

(

)

[protected]

Starts the estimation process

template<class TSample >

ComponentMembershipFunctionType* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetComponentMembershipFunction

(

int

componentIndex

)

const

Gets the membership function specified by componentIndex argument.

template<class TSample >

int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetCurrentIteration

(

)

[inline]

Gets the current iteration.

Definition at line 143 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

const ProportionVectorType& itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetInitialProportions

(

)

const

template<class TSample >

int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetMaximumIteration

(

)

const

template<class TSample >

const MembershipFunctionsWeightsArrayObjectType* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetMembershipFunctionsWeightsArray

(

)

const

Get method for data decorated Membership functions weights array

template<class TSample >

virtual const char* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetNameOfClass

(

)

const [virtual]

Standard macros

Reimplemented from itk::Object.

template<class TSample >

unsigned int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetNumberOfComponents

(

)

const

Gets the total number of classes currently plugged in.

template<class TSample >

const MembershipFunctionVectorObjectType* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetOutput

(

)

const

Output Membership function vector containing the membership functions with the final optimized parameters

template<class TSample >

const ProportionVectorType& itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetProportions

(

)

const

Gets the result proportion values

template<class TSample >

const TSample* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetSample

(

)

const

Returns the target data

template<class TSample >

TERMINATION_CODE itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetTerminationCode

(

)

const

Gets the termination status

template<class TSample >

static Pointer itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::New

(

)

[static]

Standard macros

Reimplemented from itk::Object.

template<class TSample >

void itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const [protected, virtual]

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::Object.

template<class TSample >

void itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::SetInitialProportions

(

ProportionVectorType &

propotion

)

Set/Gets the initial proportion values. The size of proportion vector should be same as the number of component (or classes)

template<class TSample >

void itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::SetMaximumIteration

(

int

numberOfIterations

)

Set/Gets the maximum number of iterations. When the optimization process reaches the maximum number of interations, even if the class parameters aren't converged, the optimization process stops.

template<class TSample >

void itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::SetSample

(

const TSample *

sample

)

Sets the target data that will be classified by this

template<class TSample >

void itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::Update

(

)

Runs the optimization process.

template<class TSample >

bool itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::UpdateComponentParameters

(

)

[protected]

template<class TSample >

bool itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::UpdateProportions

(

)

[protected]

---

Member Data Documentation

template<class TSample >

ComponentVectorType itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_ComponentVector [private]

Definition at line 195 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_CurrentIteration [private]

Definition at line 192 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

ProportionVectorType itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_InitialProportions [private]

Definition at line 196 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_MaxIteration [private]

Definition at line 191 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

MembershipFunctionVectorObjectPointer itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_MembershipFunctionsObject [private]

Definition at line 199 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

MembershipFunctionsWeightsArrayPointer itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_MembershipFunctionsWeightArrayObject [private]

Definition at line 200 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

ProportionVectorType itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_Proportions [private]

Definition at line 197 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

const TSample* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_Sample [private]

Target data sample pointer

Definition at line 189 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample >

TERMINATION_CODE itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::m_TerminationCode [private]

Definition at line 194 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

• itkExpectationMaximizationMixtureModelEstimator.h