ITK
4.2.0
Insight Segmentation and Registration Toolkit
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#include <itkBatchSupervisedTrainingFunction.h>
Public Types | |
typedef SmartPointer< const Self > | ConstPointer |
typedef Superclass::InternalVectorType | InternalVectorType |
typedef Superclass::NetworkType | NetworkType |
typedef SmartPointer< Self > | Pointer |
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< VectorType > | InputSampleVectorType |
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 SizeValueType & | GetIterations () |
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 |
Command * | GetCommand (unsigned long tag) |
bool | GetDebug () const |
MetaDataDictionary & | GetMetaDataDictionary (void) |
const MetaDataDictionary & | GetMetaDataDictionary (void) const |
virtual unsigned long | GetMTime () const |
virtual const TimeStamp & | GetTimeStamp () 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 |
This is the itkBatchSupervisedTrainingFunction class.
Definition at line 34 of file itkBatchSupervisedTrainingFunction.h.
typedef SmartPointer<const Self> itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::ConstPointer |
Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.
Definition at line 42 of file itkBatchSupervisedTrainingFunction.h.
typedef Superclass::InternalVectorType itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::InternalVectorType |
Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.
Definition at line 51 of file itkBatchSupervisedTrainingFunction.h.
typedef Superclass::NetworkType itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::NetworkType |
Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.
Definition at line 48 of file itkBatchSupervisedTrainingFunction.h.
typedef SmartPointer<Self> itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Pointer |
Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.
Definition at line 41 of file itkBatchSupervisedTrainingFunction.h.
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.
typedef TrainingFunctionBase<TSample, TTargetVector, ScalarType> itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::Superclass |
Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.
Definition at line 40 of file itkBatchSupervisedTrainingFunction.h.
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Definition at line 63 of file itkBatchSupervisedTrainingFunction.h.
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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 >.
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Method for creation through the object factory.
Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.
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Method for creation through the object factory.
Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.
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Method to print the object.
Reimplemented from itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >.
void itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >::SetNumOfIterations | ( | SizeValueType | i | ) |
Set the number of iterations
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Definition at line 69 of file itkBatchSupervisedTrainingFunction.h.
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Definition at line 68 of file itkBatchSupervisedTrainingFunction.h.