ITK  4.2.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes
itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType > Class Template Reference

#include <itkBatchSupervisedTrainingFunction.h>

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

List of all members.

Public Types

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

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 >
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 unsigned long 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 ()

Protected Member Functions

 BatchSupervisedTrainingFunction ()
virtual void PrintSelf (std::ostream &os, Indent indent) const
virtual ~BatchSupervisedTrainingFunction ()
- Protected Member Functions inherited from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >
 TrainingFunctionBase ()
 ~TrainingFunctionBase ()
- Protected Member Functions inherited from itk::LightProcessObject
 LightProcessObject ()
 ~LightProcessObject ()
virtual void GenerateData ()
- 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

Detailed Description

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

This is the itkBatchSupervisedTrainingFunction class.

Definition at line 34 of file itkBatchSupervisedTrainingFunction.h.


Member Typedef Documentation

template<class TSample , class TTargetVector , class ScalarType >
typedef SmartPointer<const Self> itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::ConstPointer
template<class TSample , class TTargetVector , class ScalarType >
typedef Superclass::InternalVectorType itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::InternalVectorType
template<class TSample , class TTargetVector , class ScalarType >
typedef Superclass::NetworkType itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::NetworkType
template<class TSample , class TTargetVector , class ScalarType >
typedef SmartPointer<Self> itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Pointer
template<class TSample , class TTargetVector , class ScalarType >
typedef BatchSupervisedTrainingFunction itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Self

Standard class typedefs.

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

Definition at line 38 of file itkBatchSupervisedTrainingFunction.h.

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

Constructor & Destructor Documentation

template<class TSample , class TTargetVector , class ScalarType >
itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::BatchSupervisedTrainingFunction ( )
protected
template<class TSample , class TTargetVector , class ScalarType >
virtual itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::~BatchSupervisedTrainingFunction ( )
inlineprotectedvirtual

Definition at line 63 of file itkBatchSupervisedTrainingFunction.h.


Member Function Documentation

template<class TSample , class TTargetVector , class ScalarType >
virtual::itk::LightObject::Pointer itk::Statistics::BatchSupervisedTrainingFunction< 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::BatchSupervisedTrainingFunction< 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::BatchSupervisedTrainingFunction< 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::BatchSupervisedTrainingFunction< 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::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::SetNumOfIterations ( SizeValueType  i)

Set the number of iterations

template<class TSample , class TTargetVector , class ScalarType >
virtual void itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::SetThreshold ( ScalarType  _arg)
virtual
template<class TSample , class TTargetVector , class ScalarType >
virtual void itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Train ( NetworkType net,
TSample *  samples,
TTargetVector *  targets 
)
virtual

Member Data Documentation

template<class TSample , class TTargetVector , class ScalarType >
bool itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::m_Stop
protected

Definition at line 69 of file itkBatchSupervisedTrainingFunction.h.

template<class TSample , class TTargetVector , class ScalarType >
ScalarType itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::m_Threshold
protected

Definition at line 68 of file itkBatchSupervisedTrainingFunction.h.


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