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

#include <itkIterativeSupervisedTrainingFunction.h>

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

[legend]Collaboration diagram for itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >:

[legend]List of all members.

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

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

---

Member Typedef Documentation

template<class TSample, class TOutput, class ScalarType> typedef SmartPointer<const Self> itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::ConstPointer

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >. Definition at line 37 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample, class TOutput, class ScalarType> typedef Superclass::NetworkType itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::NetworkType

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >. Definition at line 45 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample, class TOutput, class ScalarType> typedef SmartPointer<Self> itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::Pointer

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >. Definition at line 36 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample, class TOutput, class ScalarType> typedef IterativeSupervisedTrainingFunction itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::Self

Standard class typedefs. Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >. Definition at line 34 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample, class TOutput, class ScalarType> typedef TrainingFunctionBase<TSample, TOutput, ScalarType> itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::Superclass

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >. Definition at line 35 of file itkIterativeSupervisedTrainingFunction.h.

---

Constructor & Destructor Documentation

template<class TSample, class TOutput, class ScalarType> itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::IterativeSupervisedTrainingFunction (   )  [protected]

template<class TSample, class TOutput, class ScalarType> itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::~IterativeSupervisedTrainingFunction (   )  [inline, protected]

Definition at line 56 of file itkIterativeSupervisedTrainingFunction.h.

---

Member Function Documentation

template<class TSample, class TOutput, class ScalarType> virtual const char* itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::GetNameOfClass (   )  const [virtual]

Method for creation through the object factory. Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >.

template<class TSample, class TOutput, class ScalarType> Pointer itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::New (   )  [static]

Method for creation through the object factory. Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >.

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

Method to print the object. Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >.

template<class TSample, class TOutput, class ScalarType> void itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::SetNumOfIterations (  long  i  )

template<class TSample, class TOutput, class ScalarType> virtual void itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::SetThreshold (  ScalarType  _arg  )  [virtual]

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

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

---

Member Data Documentation

template<class TSample, class TOutput, class ScalarType> bool itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::m_Stop [protected]

Definition at line 62 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample, class TOutput, class ScalarType> ScalarType itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TOutput, ScalarType >::m_Threshold [protected]

Definition at line 61 of file itkIterativeSupervisedTrainingFunction.h.

---

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

• itkIterativeSupervisedTrainingFunction.h

---