ITK  4.4.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | List of all members
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 >:

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.

Public Types

typedef SmartPointer< const SelfConstPointer
 
typedef
Superclass::InternalVectorType 
InternalVectorType
 
typedef Superclass::NetworkType NetworkType
 
typedef SmartPointer< SelfPointer
 
typedef
IterativeSupervisedTrainingFunction 
Self
 
typedef TrainingFunctionBase
< TSample, TTargetVector,
ScalarType > 
Superclass
 
- Public Types inherited from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >
typedef SmartPointer< const SelfConstPointer
 
typedef
SquaredDifferenceErrorFunction
< InternalVectorType,
ScalarType > 
DefaultPerformanceType
 
typedef std::vector< VectorTypeInputSampleVectorType
 
typedef Array< ValueTypeInternalVectorType
 
typedef NeuralNetworkObject
< VectorType, OutputVectorType
NetworkType
 
typedef std::vector
< OutputVectorType
OutputSampleVectorType
 
typedef
TTargetVector::MeasurementVectorType 
OutputVectorType
 
typedef ErrorFunctionBase
< InternalVectorType,
ScalarType > 
PerformanceFunctionType
 
typedef SmartPointer< SelfPointer
 
typedef TrainingFunctionBase Self
 
typedef LightProcessObject Superclass
 
typedef ScalarType ValueType
 
typedef
TSample::MeasurementVectorType 
VectorType
 
- Public Types inherited from itk::LightProcessObject
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef LightProcessObject Self
 
typedef Object Superclass
 
- Public Types inherited from itk::Object
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef Object Self
 
typedef LightObject Superclass
 
- Public Types inherited from itk::LightObject
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef LightObject Self
 

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)
 
- Public Member Functions inherited from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >
virtual ::itk::LightObject::Pointer CreateAnother (void) const
 
VectorType defaultconverter (typename TSample::MeasurementVectorType v)
 
virtual const SizeValueTypeGetIterations ()
 
ValueType GetLearningRate ()
 
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 *)
 
- Public Member Functions inherited from itk::LightProcessObject
virtual void AbortGenerateDataOff ()
 
virtual void AbortGenerateDataOn ()
 
virtual const bool & GetAbortGenerateData ()
 
virtual void SetAbortGenerateData (bool _arg)
 
virtual void UpdateOutputData ()
 
void UpdateProgress (float amount)
 
virtual void SetProgress (float _arg)
 
virtual const float & GetProgress ()
 
- Public Member Functions inherited from itk::Object
unsigned long AddObserver (const EventObject &event, Command *)
 
unsigned long AddObserver (const EventObject &event, Command *) const
 
virtual void DebugOff () const
 
virtual void DebugOn () const
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary (void)
 
const MetaDataDictionaryGetMetaDataDictionary (void) const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () const
 
bool HasObserver (const EventObject &event) const
 
void InvokeEvent (const EventObject &)
 
void InvokeEvent (const EventObject &) const
 
virtual void Modified () const
 
virtual void Register () const
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
virtual void SetReferenceCount (int)
 
virtual void UnRegister () const
 
- Public Member Functions inherited from itk::LightObject
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
 itkCloneMacro (Self)
 
void Print (std::ostream &os, Indent indent=0) const
 

Static Public Member Functions

static Pointer New ()
 
- Static Public Member Functions inherited from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >
static Pointer New ()
 
- Static Public Member Functions inherited from itk::LightProcessObject
static Pointer New ()
 
- Static Public Member Functions inherited from itk::Object
static bool GetGlobalWarningDisplay ()
 
static void GlobalWarningDisplayOff ()
 
static void GlobalWarningDisplayOn ()
 
static Pointer New ()
 
static void SetGlobalWarningDisplay (bool flag)
 
- Static Public Member Functions inherited from itk::LightObject
static void BreakOnError ()
 
static Pointer New ()
 

Protected Member Functions

 IterativeSupervisedTrainingFunction ()
 
virtual void PrintSelf (std::ostream &os, Indent indent) const
 
virtual ~IterativeSupervisedTrainingFunction ()
 
- Protected Member Functions inherited from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >
 TrainingFunctionBase ()
 
 ~TrainingFunctionBase ()
 
- Protected Member Functions inherited from itk::LightProcessObject
virtual void GenerateData ()
 
 LightProcessObject ()
 
 ~LightProcessObject ()
 
- Protected Member Functions inherited from itk::Object
 Object ()
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
virtual ~Object ()
 
- Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer InternalClone () const
 
 LightObject ()
 
virtual void PrintHeader (std::ostream &os, Indent indent) const
 
virtual void PrintTrailer (std::ostream &os, Indent indent) const
 
virtual ~LightObject ()
 

Protected Attributes

bool m_Stop
 
ScalarType m_Threshold
 
- Protected Attributes inherited from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >
InputSampleVectorType m_InputSamples
 
SizeValueType m_Iterations
 
ValueType m_LearningRate
 
PerformanceFunctionType::Pointer m_PerformanceFunction
 
TTargetVector * m_SampleTargets
 
OutputSampleVectorType m_Targets
 
TSample * m_TrainingSamples
 

Additional Inherited Members

- Protected Types inherited from itk::LightObject
typedef int InternalReferenceCountType
 

Member Typedef Documentation

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

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

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

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

Definition at line 40 of file itkIterativeSupervisedTrainingFunction.h.

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

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

Definition at line 39 of file itkIterativeSupervisedTrainingFunction.h.

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 ( )
inlineprotectedvirtual

Definition at line 61 of file itkIterativeSupervisedTrainingFunction.h.

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::LightProcessObject.

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.

template<class TSample , class TTargetVector , class ScalarType >
virtual void itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
protectedvirtual

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

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.


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