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 >:

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[NOHEADER]
virtual const char *	GetClassName () const
Pointer	New ()
Public Types
typedef ExpectationMaximizationMixtureModelEstimator	Self
typedef Object	Superclass
typedef SmartPointer< Self >	Pointer
typedef TSample::MeasurementType	MeasurementType
typedef TSample::MeasurementVectorType	MeasurementVectorType
typedef MixtureModelComponentBase< TSample >	ComponentType
typedef std::vector< ComponentType * >	ComponentVectorType
typedef MembershipFunctionBase< MeasurementVectorType >	ComponentMembershipFunctionType
typedef Array< double >	ProportionVectorType
enum	TERMINATION_CODE { CONVERGED = 0, NOT_CONVERGED = 1 }
Public Member Functions
	itkStaticConstMacro (MeasurementVectorSize, unsigned int, TSample::MeasurementVectorSize)
void	SetSample (TSample *sample)
TSample *	GetSample ()
ProportionVectorType *	GetProportions ()
int	GetCurrentIteration ()
int	AddComponent (ComponentType *component)
int	GetNumberOfComponents ()
void	Update ()
TERMINATION_CODE	GetTerminationCode ()
ComponentMembershipFunctionType *	GetComponentMembershipFunction (int componentIndex)
void	SetInitialProportions (ProportionVectorType &propotion)
ProportionVectorType *	GetInitialProportions ()
void	SetMaximumIteration (int numberOfIterations)
int	GetMaximumIteration ()
Protected Member Functions
	ExpectationMaximizationMixtureModelEstimator ()
virtual	~ExpectationMaximizationMixtureModelEstimator ()
void	PrintSelf (std::ostream &os, Indent indent) const
bool	CalculateDensities ()
double	CalculateExpectation ()
bool	UpdateComponentParameters ()
bool	UpdateProportions ()
void	GenerateData ()

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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.

See also:

MixtureModelComponentBase, GaussianMixtureModelComponent

Definition at line 46 of file itkExpectationMaximizationMixtureModelEstimator.h.

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Member Typedef Documentation

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

Type of the membership function base class Definition at line 76 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 69 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 72 of file itkExpectationMaximizationMixtureModelEstimator.h. Referenced by itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::~ExpectationMaximizationMixtureModelEstimator().

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

TSample template argument related typedefs Definition at line 65 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

Definition at line 66 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

Reimplemented from itk::Object. Definition at line 52 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 79 of file itkExpectationMaximizationMixtureModelEstimator.h. Referenced by itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::~ExpectationMaximizationMixtureModelEstimator().

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

Standard class typedef Reimplemented from itk::Object. Definition at line 50 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

Reimplemented from itk::Object. Definition at line 51 of file itkExpectationMaximizationMixtureModelEstimator.h.

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Member Enumeration Documentation

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

Termination status after running optimization Enumeration values: CONVERGED  NOT_CONVERGED  Definition at line 118 of file itkExpectationMaximizationMixtureModelEstimator.h.

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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 129 of file itkExpectationMaximizationMixtureModelEstimator.h. References itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::ComponentVectorType, and itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::ProportionVectorType.

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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 (   )  [protected]

template<class TSample> void itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GenerateData (   )  [protected]

Starts the estimation process

template<class TSample> virtual const char* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetClassName (   )  const [virtual]

Standard macros Reimplemented from itk::Object.

template<class TSample> ComponentMembershipFunctionType* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetComponentMembershipFunction (  int  componentIndex  )

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 105 of file itkExpectationMaximizationMixtureModelEstimator.h.

template<class TSample> ProportionVectorType* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetInitialProportions (   )

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

template<class TSample> int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetMaximumIteration (   )

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> int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetNumberOfComponents (   )

Gets the total number of classes currently plugged in.

template<class TSample> ProportionVectorType* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetProportions (   )

Gets the result proportion values

template<class TSample> TSample* itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetSample (   )

Returns the target data

template<class TSample> TERMINATION_CODE itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetTerminationCode (   )

Gets the termination status

template<class TSample> itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::itkStaticConstMacro (  MeasurementVectorSize  , unsigned  int, TSample::MeasurementVectorSize  )

Length constant

template<class TSample> 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 (  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]

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

• itkExpectationMaximizationMixtureModelEstimator.h

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