ITK  4.1.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes
itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType > Class Template Reference
Module ITKNeuralNetworks

#include <itkTrainingFunctionBase.h>

+ Inheritance diagram for itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >:
+ Collaboration diagram for itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >:

List of all members.

Public Types

typedef SmartPointer< const Self > ConstPointer
typedef
SquaredDifferenceErrorFunction
< InternalVectorType,
ScalarType > 		DefaultPerformanceType
typedef std::vector< VectorType > InputSampleVectorType
typedef Array< ValueType > InternalVectorType
typedef NeuralNetworkObject
< VectorType, OutputVectorType > 		NetworkType
typedef std::vector
< OutputVectorType > 		OutputSampleVectorType
typedef
TTargetVector::MeasurementVectorType 		OutputVectorType
typedef ErrorFunctionBase
< InternalVectorType,
ScalarType > 		PerformanceFunctionType
typedef SmartPointer< Self > Pointer
typedef TrainingFunctionBase Self
typedef LightProcessObject Superclass
typedef ScalarType ValueType
typedef
TSample::MeasurementVectorType 		VectorType

Public Member Functions

virtual ::itk::LightObject::Pointer CreateAnother (void) const
VectorType defaultconverter (typename TSample::MeasurementVectorType v)
virtual const SizeValueType & GetIterations ()
ValueType GetLearningRate ()
virtual const char * GetNameOfClass () const
virtual void SetIterations (SizeValueType _arg)
void SetLearningRate (ValueType)
void SetPerformanceFunction (PerformanceFunctionType *f)
void SetTargetValues (TTargetVector *targets)
void SetTrainingSamples (TSample *samples)
OutputVectorType targetconverter (typename TTargetVector::MeasurementVectorType v)
virtual void Train (NetworkType *, TSample *, TTargetVector *)

Static Public Member Functions

static Pointer New ()

Protected Member Functions

virtual void PrintSelf (std::ostream &os, Indent indent) const
 TrainingFunctionBase ()
 ~TrainingFunctionBase ()

Protected Attributes

InputSampleVectorType m_InputSamples
SizeValueType m_Iterations
ValueType m_LearningRate
PerformanceFunctionType::Pointer m_PerformanceFunction
TTargetVector * m_SampleTargets
OutputSampleVectorType m_Targets
TSample * m_TrainingSamples

Detailed Description

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

This is the itkTrainingFunctionBase class.

Definition at line 37 of file itkTrainingFunctionBase.h.

Member Typedef Documentation

template<class TSample , class TTargetVector , class ScalarType >
typedef SmartPointer<const Self> itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::ConstPointer

Reimplemented from itk::LightProcessObject.

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

Definition at line 43 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef SquaredDifferenceErrorFunction<InternalVectorType, ScalarType> itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::DefaultPerformanceType

Definition at line 61 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef std::vector<VectorType> itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::InputSampleVectorType

Definition at line 56 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef Array<ValueType> itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::InternalVectorType

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

Definition at line 54 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef NeuralNetworkObject<VectorType, OutputVectorType> itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::NetworkType

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

Definition at line 58 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef std::vector<OutputVectorType> itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::OutputSampleVectorType

Definition at line 57 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef TTargetVector::MeasurementVectorType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::OutputVectorType

Definition at line 53 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef ErrorFunctionBase<InternalVectorType, ScalarType> itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::PerformanceFunctionType

Definition at line 59 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef SmartPointer<Self> itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::Pointer

Reimplemented from itk::LightProcessObject.

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

Definition at line 42 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef TrainingFunctionBase itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::Self

Standard class typedefs.

Reimplemented from itk::LightProcessObject.

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

Definition at line 40 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef LightProcessObject itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::Superclass

Reimplemented from itk::LightProcessObject.

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

Definition at line 41 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef ScalarType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::ValueType

Definition at line 49 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
typedef TSample::MeasurementVectorType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::VectorType

Definition at line 52 of file itkTrainingFunctionBase.h.

Constructor & Destructor Documentation

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

Definition at line 105 of file itkTrainingFunctionBase.h.

Member Function Documentation

template<class TSample , class TTargetVector , class ScalarType >
virtual::itk::LightObject::Pointer itk::Statistics::TrainingFunctionBase< 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::LightProcessObject.

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

template<class TSample , class TTargetVector , class ScalarType >
VectorType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::defaultconverter ( typename TSample::MeasurementVectorType  v) [inline]

Definition at line 80 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
virtual const SizeValueType& itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::GetIterations ( ) [virtual]
template<class TSample , class TTargetVector , class ScalarType >
ValueType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::GetLearningRate ( )
template<class TSample , class TTargetVector , class ScalarType >
virtual const char* itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::GetNameOfClass ( ) const [virtual]

Method for creation through the object factory.

Reimplemented from itk::LightProcessObject.

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

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

Method for creation through the object factory.

Reimplemented from itk::LightProcessObject.

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

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

Method to print the object.

Reimplemented from itk::LightProcessObject.

Reimplemented in itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >, and itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >.

template<class TSample , class TTargetVector , class ScalarType >
virtual void itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::SetIterations ( SizeValueType  _arg) [virtual]
template<class TSample , class TTargetVector , class ScalarType >
void itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::SetLearningRate ( ValueType  )
template<class TSample , class TTargetVector , class ScalarType >
void itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::SetPerformanceFunction ( PerformanceFunctionType *  f)
template<class TSample , class TTargetVector , class ScalarType >
void itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::SetTargetValues ( TTargetVector *  targets)
template<class TSample , class TTargetVector , class ScalarType >
void itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::SetTrainingSamples ( TSample *  samples)
template<class TSample , class TTargetVector , class ScalarType >
OutputVectorType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::targetconverter ( typename TTargetVector::MeasurementVectorType  v) [inline]

Definition at line 91 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
virtual void itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::Train ( NetworkType *  ,
TSample *  ,
TTargetVector *   
) [inline, virtual]

Definition at line 74 of file itkTrainingFunctionBase.h.

Member Data Documentation

template<class TSample , class TTargetVector , class ScalarType >
InputSampleVectorType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::m_InputSamples [protected]

Definition at line 112 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
SizeValueType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::m_Iterations [protected]

Definition at line 114 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
ValueType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::m_LearningRate [protected]

Definition at line 115 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
PerformanceFunctionType::Pointer itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::m_PerformanceFunction [protected]

Definition at line 117 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
TTargetVector* itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::m_SampleTargets [protected]

Definition at line 111 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
OutputSampleVectorType itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::m_Targets [protected]

Definition at line 113 of file itkTrainingFunctionBase.h.

template<class TSample , class TTargetVector , class ScalarType >
TSample* itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >::m_TrainingSamples [protected]

Definition at line 110 of file itkTrainingFunctionBase.h.

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