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

Integration point for MembershipCalculator, DecisionRule, and target sample data. More...

#include <itkExpectationMaximizationMixtureModelEstimator.h>

Inheritance diagram for itk::Statistics::ExpectationMaximizationMixtureModelEstimator:

[legend]Collaboration diagram for itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >:

[legend]List of all members.

[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 Methods
	itkStaticConstMacro (MeasurementVectorSize, unsigned int, TSample::MeasurementVectorSize)
void	SetSample (TSample *sample)
TSample *	GetSample ()
void	SetInitialProportions (ProportionVectorType &propotion)
ProportionVectorType *	GetInitialProportions ()
ProportionVectorType *	GetProportions ()
void	SetMaximumIteration (int numberOfIterations)
int	GetMaximumIteration ()
int	GetCurrentIteration ()
int	AddComponent (ComponentType *component)
int	GetNumberOfComponents ()
void	Update ()
TERMINATION_CODE	GetTerminationCode ()
ComponentMembershipFunctionType *	GetComponentMembershipFunction (int componentIndex)
Protected Methods
	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 >

Integration point for MembershipCalculator, DecisionRule, and target sample data.

The first template argument is the type of the target sample data that this classifier will assign a class label for each measurement vector. The second one is the type of a membership value calculator for each. A membership calculator represents a specific knowledge about a class. In other words, it should tell us how "likely" is that a measurement vector (pattern) belong to the class. The third argument is the type of decision rule. The main role of a decision rule is comparing the return values of the membership calculators. However, decision rule can include some prior knowledge that can improve the result.

Before you call the GenerateData method to start the classification process, you should plug in all necessary parts ( one or more membership calculators, a decision rule, and a target sample data). To plug in the decision rule, you use SetDecisionRule method, for the target sample data, SetSample method, and for the membership calculators, use AddMembershipCalculator method.

As the method name indicates, you can have more than one membership calculator. One for each classes. The order you put the membership calculator becomes the class label for the class that is represented by the membership calculator.

The classification result is stored in a vector of Subsample object. Each class has its own class sample (Subsample object) that has InstanceIdentifiers for all measurement vectors belong to the class. The InstanceIdentifiers come from the target sample data. Therefore, the Subsample objects act as separate class masks.

Definition at line 61 of file itkExpectationMaximizationMixtureModelEstimator.h.

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Member Typedef Documentation

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

Definition at line 85 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

Definition at line 83 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

Definition at line 84 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

TSample template argument related typedefs Definition at line 80 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

Definition at line 81 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

Definition at line 93 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.

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Member Enumeration Documentation

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

Enumeration values: CONVERGED  NOT_CONVERGED  Definition at line 114 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 121 of file itkExpectationMaximizationMixtureModelEstimator.h. References HardConnectedComponentImageFilter::GenerateData(), and HardConnectedComponentImageFilter::PrintSelf().

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Member Function Documentation

template<class TSample> int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::AddComponent (  ComponentType *    component )

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 classification 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 )

template<class TSample> int itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::GetCurrentIteration (    )  [inline]

Definition at line 105 of file itkExpectationMaximizationMixtureModelEstimator.h.

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

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

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

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

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

Returns the target data

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

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 )

template<class TSample> void itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >::SetMaximumIteration (  int    numberOfIterations )

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 (    )

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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