itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType > Class Template Reference

#include <itkIterativeSupervisedTrainingFunction.h>

Inheritance diagram for itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >:

Collaboration diagram for itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >:

List of all members.

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef Superclass::InternalVectorType	InternalVectorType
typedef Superclass::NetworkType	NetworkType
typedef SmartPointer< Self >	Pointer
typedef IterativeSupervisedTrainingFunction	Self
typedef TrainingFunctionBase < TSample, TTargetVector, ScalarType >	Superclass
Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
virtual const char *	GetNameOfClass () const
void	SetNumOfIterations (SizeValueType i)
virtual void	SetThreshold (ScalarType _arg)
virtual void	Train (NetworkType *net, TSample *samples, TTargetVector *targets)
Static Public Member Functions
static Pointer	New ()
Protected Member Functions
	IterativeSupervisedTrainingFunction ()
virtual void	PrintSelf (std::ostream &os, Indent indent) const
virtual	~IterativeSupervisedTrainingFunction ()
Protected Attributes
bool	m_Stop
ScalarType	m_Threshold

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Detailed Description

template<class TSample, class TTargetVector, class ScalarType>
class itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >

This is the itkIterativeSupervisedTrainingFunction class.

Definition at line 34 of file itkIterativeSupervisedTrainingFunction.h.

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Member Typedef Documentation

template<class TSample , class TTargetVector , class ScalarType >

typedef SmartPointer<const Self> itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::ConstPointer

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

Definition at line 41 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample , class TTargetVector , class ScalarType >

typedef Superclass::InternalVectorType itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::InternalVectorType

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

Definition at line 50 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample , class TTargetVector , class ScalarType >

typedef Superclass::NetworkType itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::NetworkType

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

Definition at line 47 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample , class TTargetVector , class ScalarType >

typedef SmartPointer<Self> itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Pointer

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

Definition at line 40 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample , class TTargetVector , class ScalarType >

typedef IterativeSupervisedTrainingFunction itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Self

Standard class typedefs.

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

Definition at line 38 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample , class TTargetVector , class ScalarType >

typedef TrainingFunctionBase<TSample, TTargetVector, ScalarType> itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Superclass

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

Definition at line 39 of file itkIterativeSupervisedTrainingFunction.h.

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Constructor & Destructor Documentation

template<class TSample , class TTargetVector , class ScalarType >

itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::IterativeSupervisedTrainingFunction

(

)

[protected]

template<class TSample , class TTargetVector , class ScalarType >

virtual itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::~IterativeSupervisedTrainingFunction

(

)

[inline, protected, virtual]

Definition at line 61 of file itkIterativeSupervisedTrainingFunction.h.

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Member Function Documentation

template<class TSample , class TTargetVector , class ScalarType >

virtual::itk::LightObject::Pointer itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::CreateAnother

(

void

)

const [virtual]

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

template<class TSample , class TTargetVector , class ScalarType >

virtual const char* itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::GetNameOfClass

(

)

const [virtual]

Method for creation through the object factory.

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

template<class TSample , class TTargetVector , class ScalarType >

static Pointer itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::New

(

)

[static]

Method for creation through the object factory.

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

template<class TSample , class TTargetVector , class ScalarType >

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

Method to print the object.

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.

template<class TSample , class TTargetVector , class ScalarType >

void itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::SetNumOfIterations

(

SizeValueType

i

)

template<class TSample , class TTargetVector , class ScalarType >

virtual void itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::SetThreshold

(

ScalarType

_arg

)

[virtual]

template<class TSample , class TTargetVector , class ScalarType >

virtual void itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Train	(	NetworkType *	net,
		TSample *	samples,
		TTargetVector *	targets
	)		[virtual]

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Member Data Documentation

template<class TSample , class TTargetVector , class ScalarType >

bool itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::m_Stop [protected]

Definition at line 67 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample , class TTargetVector , class ScalarType >

ScalarType itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::m_Threshold [protected]

Definition at line 66 of file itkIterativeSupervisedTrainingFunction.h.

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

• itkIterativeSupervisedTrainingFunction.h