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.

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

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef SquaredDifferenceErrorFunction< InternalVectorType, ScalarType >	DefaultPerformanceType
typedef std::vector< VectorType >	InputSampleVectorType
typedef Superclass::InternalVectorType	InternalVectorType
typedef Superclass::NetworkType	NetworkType
typedef std::vector< OutputVectorType >	OutputSampleVectorType
typedef TOutput::MeasurementVectorType	OutputVectorType
typedef ErrorFunctionBase< InternalVectorType, ScalarType >	PerformanceFunctionType
typedef SmartPointer< Self >	Pointer
typedef IterativeSupervisedTrainingFunction	Self
typedef TrainingFunctionBase< TSample, TOutput, ScalarType >	Superclass
typedef ScalarType	ValueType
typedef TSample::MeasurementVectorType	VectorType
Public Member Functions
virtual void	AbortGenerateDataOff ()
virtual void	AbortGenerateDataOn ()
Get the execution progress of a process object The progress is *a floating number	between (0, 1)
Set the execution progress of a process object The progress is *a floating number	between (0, 1)
virtual LightObject::Pointer	CreateAnother () const
virtual void	DebugOff () const
virtual void	DebugOn () const
VectorType	defaultconverter (typename TSample::MeasurementVectorType v)
virtual void	Delete ()
virtual const bool &	GetAbortGenerateData ()
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
virtual const long &	GetIterations ()
ValueType	GetLearningRate ()
const MetaDataDictionary &	GetMetaDataDictionary (void) const
MetaDataDictionary &	GetMetaDataDictionary (void)
virtual unsigned long	GetMTime () const
virtual const char *	GetNameOfClass () const
meaning *the filter has completed execution *virtual const float &	GetProgress ()
virtual int	GetReferenceCount () const
bool	HasObserver (const EventObject &event) const
void	InvokeEvent (const EventObject &) const
void	InvokeEvent (const EventObject &)
virtual void	Modified () const
void	Print (std::ostream &os, Indent indent=0) const
virtual void	Register () const
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
virtual void	SetAbortGenerateData (bool _arg)
void	SetDebug (bool debugFlag) const
virtual void	SetIterations (long _arg)
void	SetLearningRate (ValueType)
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
void	SetNumOfIterations (long i)
void	SetPerformanceFunction (PerformanceFunctionType *f)
meaning *the filter has completed execution *virtual void	SetProgress (float _arg)
virtual void	SetReferenceCount (int)
void	SetTargetValues (TOutput *targets)
virtual void	SetThreshold (ScalarType _arg)
void	SetTrainingSamples (TSample *samples)
OutputVectorType	targetconverter (typename TOutput::MeasurementVectorType v)
void	Train (NetworkType *net, TSample *samples, TOutput *targets)
virtual void	UnRegister () const
virtual void	UpdateOutputData ()
void	UpdateProgress (float amount)
Static Public Member Functions
static void	BreakOnError ()
static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static Pointer	New ()
This is a global flag that controls whether any warning *or error messages are displayed *static void	SetGlobalWarningDisplay (bool flag)
Public Attributes
Allow people to add remove invoke observers(callbacks) to any ITK *object.This is an implementation of the subject/observer design *pattern.An observer is added by specifying an event to respond to *and an itk unsigned lon	AddObserver )(const EventObject &event, Command *) const
This is a global flag that controls whether any	debug
Get the execution progress of a process object The progress is *a floating number meaning no	progress
Set the execution progress of a process object The progress is *a floating number meaning no	progress
Protected Member Functions
virtual void	GenerateData ()
	IterativeSupervisedTrainingFunction ()
bool	PrintObservers (std::ostream &os, Indent indent) const
virtual void	PrintSelf (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const
	~IterativeSupervisedTrainingFunction ()
Protected Attributes
InputSampleVectorType	m_InputSamples
long	m_Iterations
ValueType	m_LearningRate
PerformanceFunctionType::Pointer	m_PerformanceFunction
int	m_ReferenceCount
SimpleFastMutexLock	m_ReferenceCountLock
TOutput *	m_SampleTargets
bool	m_Stop
OutputSampleVectorType	m_Targets
ScalarType	m_Threshold
TSample *	m_TrainingSamples
Methods invoked by virtual Print() to print information about the object *including superclasses.Typically not called by the user(use Print()*instead) but used in the hierarchical print process to combine the *output of several classes.*/virtual void PrintSelf(std voi	PrintHeader )(std::ostream &os, Indent indent) const

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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 SquaredDifferenceErrorFunction<InternalVectorType, ScalarType> itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::DefaultPerformanceType [inherited]

Definition at line 55 of file itkTrainingFunctionBase.h.

template<class TSample, class TOutput, class ScalarType> typedef std::vector<VectorType> itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::InputSampleVectorType [inherited]

Definition at line 51 of file itkTrainingFunctionBase.h.

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

Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >. Definition at line 46 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 43 of file itkIterativeSupervisedTrainingFunction.h.

template<class TSample, class TOutput, class ScalarType> typedef std::vector<OutputVectorType> itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::OutputSampleVectorType [inherited]

Definition at line 52 of file itkTrainingFunctionBase.h.

template<class TSample, class TOutput, class ScalarType> typedef TOutput::MeasurementVectorType itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::OutputVectorType [inherited]

Definition at line 48 of file itkTrainingFunctionBase.h.

template<class TSample, class TOutput, class ScalarType> typedef ErrorFunctionBase<InternalVectorType, ScalarType> itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::PerformanceFunctionType [inherited]

Definition at line 54 of file itkTrainingFunctionBase.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.

template<class TSample, class TOutput, class ScalarType> typedef ScalarType itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::ValueType [inherited]

Definition at line 44 of file itkTrainingFunctionBase.h.

template<class TSample, class TOutput, class ScalarType> typedef TSample::MeasurementVectorType itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::VectorType [inherited]

Definition at line 47 of file itkTrainingFunctionBase.h.

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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 57 of file itkIterativeSupervisedTrainingFunction.h.

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Member Function Documentation

virtual void itk::LightProcessObject::AbortGenerateDataOff (   )  [virtual, inherited]

virtual void itk::LightProcessObject::AbortGenerateDataOn (   )  [virtual, inherited]

Turn on and off the AbortGenerateData flag.

Get the execution progress of a process object The progress is* a floating number itk::LightProcessObject::between (  0  , 1  )  [inherited]

Set the execution progress of a process object The progress is* a floating number itk::LightProcessObject::between (  0  , 1  )  [inherited]

static void itk::LightObject::BreakOnError (   )  [static, inherited]

This method is called when itkExceptionMacro executes. It allows the debugger to break on error.

virtual LightObject::Pointer itk::Object::CreateAnother (   )  const [virtual, inherited]

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::LightObject.

virtual void itk::Object::DebugOff (   )  const [virtual, inherited]

Turn debugging output off.

virtual void itk::Object::DebugOn (   )  const [virtual, inherited]

Turn debugging output on.

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

Definition at line 76 of file itkTrainingFunctionBase.h.

virtual void itk::LightObject::Delete (   )  [virtual, inherited]

Delete an itk object. This method should always be used to delete an object when the new operator was used to create it. Using the C delete method will not work with reference counting.

virtual void itk::LightProcessObject::GenerateData (  void   )  [inline, protected, virtual, inherited]

This method causes the filter to generate its output. Reimplemented in itk::ClassifierBase< TDataContainer >, itk::ImageClassifierBase< TInputImage, TClassifiedImage >, itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >, itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >, itk::LevelSetNeighborhoodExtractor< TLevelSet >, itk::Statistics::SampleClassifier< TSample >, itk::Statistics::SampleClassifierWithMask< TSample, TMaskSample >, itk::ClassifierBase< TInputImage >, and itk::ClassifierBase< TSample >. Definition at line 123 of file itkLightProcessObject.h.

virtual const bool& itk::LightProcessObject::GetAbortGenerateData (   )  [virtual, inherited]

Get the AbortGenerateData flag for the process object. Process objects may handle premature termination of execution in different ways.

Command* itk::Object::GetCommand (  unsigned long  tag  )  [inherited]

Get the command associated with the given tag. NOTE: This returns a pointer to a Command, but it is safe to asign this to a Command::Pointer. Since Command inherits from LightObject, at this point in the code, only a pointer or a reference to the Command can be used.

bool itk::Object::GetDebug (   )  const [inherited]

Get the value of the debug flag.

static bool itk::Object::GetGlobalWarningDisplay (   )  [static, inherited]

template<class TSample, class TOutput, class ScalarType> virtual const long& itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::GetIterations (   )  [virtual, inherited]

template<class TSample, class TOutput, class ScalarType> ValueType itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::GetLearningRate (   )  [inherited]

const MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  const [inherited]

Returns: A constant reference to this objects MetaDataDictionary.

MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  [inherited]

Returns: A reference to this objects MetaDataDictionary. Warning: This reference may be changed.

virtual unsigned long itk::Object::GetMTime (   )  const [virtual, inherited]

Return this objects modified time. Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::SceneSpatialObject< SpaceDimension >, and itk::SceneSpatialObject< NDimensions >.

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 >.

meaning* the filter has completed execution* virtual const float& itk::LightProcessObject::GetProgress (   )  [virtual, inherited]

virtual int itk::LightObject::GetReferenceCount (   )  const [inline, virtual, inherited]

Gets the reference count on this object. Definition at line 98 of file itkLightObject.h.

static void itk::Object::GlobalWarningDisplayOff (   )  [inline, static, inherited]

Definition at line 100 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

static void itk::Object::GlobalWarningDisplayOn (   )  [inline, static, inherited]

Definition at line 98 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

bool itk::Object::HasObserver (  const EventObject &  event  )  const [inherited]

Return true if an observer is registered for this event.

void itk::Object::InvokeEvent (  const EventObject &   )  const [inherited]

Call Execute on all the Commands observing this event id. The actions triggered by this call doesn't modify this object.

void itk::Object::InvokeEvent (  const EventObject &   )  [inherited]

Call Execute on all the Commands observing this event id.

virtual void itk::Object::Modified (   )  const [virtual, inherited]

Update the modification time for this object. Many filters rely on the modification time to determine if they need to recompute their data. Referenced by itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::HistogramAlgorithmBase< TInputHistogram >::SetInputHistogram(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints1(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints2(), itk::NonUniformBSpline< TDimension >::SetSplineOrder(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< typename ComponentType::HistogramType >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

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

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

void itk::LightObject::Print (  std::ostream &  os, Indent  indent = 0 )  const [inherited]

Cause the object to print itself out.

bool itk::Object::PrintObservers (  std::ostream &  os, Indent  indent )  const [protected, inherited]

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 >.

virtual void itk::LightObject::PrintTrailer (  std::ostream &  os, Indent  indent )  const [protected, virtual, inherited]

virtual void itk::Object::Register (   )  const [virtual, inherited]

Increase the reference count (mark as used by another object). Reimplemented from itk::LightObject.

void itk::Object::RemoveAllObservers (   )  [inherited]

Remove all observers .

void itk::Object::RemoveObserver (  unsigned long  tag  )  [inherited]

Remove the observer with this tag value.

virtual void itk::LightProcessObject::SetAbortGenerateData (  bool  _arg  )  [virtual, inherited]

Set the AbortGenerateData flag for the process object. Process objects may handle premature termination of execution in different ways.

void itk::Object::SetDebug (  bool  debugFlag  )  const [inherited]

Set the value of the debug flag. A non-zero value turns debugging on.

This is a global flag that controls whether any warning* or error messages are displayed* static void itk::Object::SetGlobalWarningDisplay (  bool  flag  )  [static, inherited]

Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().

template<class TSample, class TOutput, class ScalarType> virtual void itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::SetIterations (  long  _arg  )  [virtual, inherited]

template<class TSample, class TOutput, class ScalarType> void itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::SetLearningRate (  ValueType   )  [inherited]

void itk::Object::SetMetaDataDictionary (  const MetaDataDictionary &  rhs  )  [inherited]

Returns: Set the MetaDataDictionary

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

template<class TSample, class TOutput, class ScalarType> void itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::SetPerformanceFunction (  PerformanceFunctionType *  f  )  [inherited]

meaning* the filter has completed execution* virtual void itk::LightProcessObject::SetProgress (  float  _arg  )  [virtual, inherited]

virtual void itk::Object::SetReferenceCount (  int   )  [virtual, inherited]

Sets the reference count (use with care) Reimplemented from itk::LightObject.

template<class TSample, class TOutput, class ScalarType> void itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::SetTargetValues (  TOutput *  targets  )  [inherited]

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::TrainingFunctionBase< TSample, TOutput, ScalarType >::SetTrainingSamples (  TSample *  samples  )  [inherited]

template<class TSample, class TOutput, class ScalarType> OutputVectorType itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::targetconverter (  typename TOutput::MeasurementVectorType  v  )  [inline, inherited]

Definition at line 87 of file itkTrainingFunctionBase.h.

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 >.

virtual void itk::Object::UnRegister (   )  const [virtual, inherited]

Decrease the reference count (release by another object). Reimplemented from itk::LightObject.

virtual void itk::LightProcessObject::UpdateOutputData (   )  [virtual, inherited]

Actually generate new output.

void itk::LightProcessObject::UpdateProgress (  float  amount  )  [inherited]

Update the progress of the process object. If a ProgressMethod exists, executes it. Then set the Progress ivar to amount. The parameter amount should range between (0,1).

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Member Data Documentation

Allow people to add remove invoke observers (callbacks) to any ITK * object. This is an implementation of the subject/observer design * pattern. An observer is added by specifying an event to respond to * and an itk unsigned lon itk::Object::AddObserver)(const EventObject &event, Command *) const [inherited]

This is a global flag that controls whether any itk::Object::debug [inherited]

Definition at line 94 of file itkObject.h.

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

Definition at line 108 of file itkTrainingFunctionBase.h.

template<class TSample, class TOutput, class ScalarType> long itk::Statistics::TrainingFunctionBase< TSample, TOutput, ScalarType >::m_Iterations [protected, inherited]

Definition at line 110 of file itkTrainingFunctionBase.h.

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

Definition at line 111 of file itkTrainingFunctionBase.h.

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

Definition at line 112 of file itkTrainingFunctionBase.h.

int itk::LightObject::m_ReferenceCount [mutable, protected, inherited]

Number of uses of this object by other objects. Definition at line 119 of file itkLightObject.h.

SimpleFastMutexLock itk::LightObject::m_ReferenceCountLock [mutable, protected, inherited]

Mutex lock to protect modification to the reference count Definition at line 122 of file itkLightObject.h.

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

Definition at line 107 of file itkTrainingFunctionBase.h.

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

Definition at line 63 of file itkIterativeSupervisedTrainingFunction.h.

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

Definition at line 109 of file itkTrainingFunctionBase.h.

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

Definition at line 62 of file itkIterativeSupervisedTrainingFunction.h.

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

Definition at line 106 of file itkTrainingFunctionBase.h.

Methods invoked by virtual Print () to print information about the object * including superclasses. Typically not called by the user (use Print() * instead) but used in the hierarchical print process to combine the * output of several classes. */ virtual void PrintSelf(std voi itk::LightObject::PrintHeader)(std::ostream &os, Indent indent) const [protected, inherited]

Get the execution progress of a process object The progress is* a floating number meaning no itk::LightProcessObject::progress [inherited]

Definition at line 104 of file itkLightProcessObject.h.

Set the execution progress of a process object The progress is* a floating number meaning no itk::LightProcessObject::progress [inherited]

Definition at line 98 of file itkLightProcessObject.h.

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

• itkIterativeSupervisedTrainingFunction.h

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