#include <otbBoostMachineLearningModel.h>

Inheritance diagram for otb::BoostMachineLearningModel< TInputValue, TTargetValue >:

Collaboration diagram for otb::BoostMachineLearningModel< TInputValue, TTargetValue >:

Public Types
typedef Superclass::ConfidenceValueType	ConfidenceValueType

typedef itk::SmartPointer< const Self >	ConstPointer

typedef Superclass::InputListSampleType	InputListSampleType

typedef Superclass::InputSampleType	InputSampleType

typedef Superclass::InputValueType	InputValueType

typedef itk::SmartPointer< Self >	Pointer

typedef Superclass::ProbaSampleType	ProbaSampleType

typedef BoostMachineLearningModel	Self

typedef MachineLearningModel< TInputValue, TTargetValue >	Superclass

typedef Superclass::TargetListSampleType	TargetListSampleType

typedef Superclass::TargetSampleType	TargetSampleType

typedef Superclass::TargetValueType	TargetValueType

Public Types inherited from otb::MachineLearningModel< TInputValue, TTargetValue >
typedef MachineLearningModel	Self

typedef itk::Object	Superclass

typedef itk::SmartPointer< Self >	Pointer

typedef itk::SmartPointer< const Self >	ConstPointer

typedef MLMSampleTraits< TInputValue >::ValueType	InputValueType

typedef MLMSampleTraits< TInputValue >::SampleType	InputSampleType

typedef itk::Statistics::ListSample< InputSampleType >	InputListSampleType

typedef MLMTargetTraits< TTargetValue >::ValueType	TargetValueType

typedef MLMTargetTraits< TTargetValue >::SampleType	TargetSampleType

typedef itk::Statistics::ListSample< TargetSampleType >	TargetListSampleType

typedef MLMTargetTraits< double >::ValueType	ConfidenceValueType

typedef MLMTargetTraits< double >::SampleType	ConfidenceSampleType

typedef itk::Statistics::ListSample< ConfidenceSampleType >	ConfidenceListSampleType

typedef itk::VariableLengthVector< double >	ProbaSampleType

typedef itk::Statistics::ListSample< ProbaSampleType >	ProbaListSampleType

static Pointer	New ()

virtual ::itk::LightObject::Pointer	CreateAnother (void) const

virtual const char *	GetNameOfClass () const

virtual int	GetBoostType ()

virtual void	SetBoostType (int _arg)

virtual int	GetWeakCount ()

virtual void	SetWeakCount (int _arg)

virtual double	GetWeightTrimRate ()

virtual void	SetWeightTrimRate (double _arg)

virtual int	GetMaxDepth ()

virtual void	SetMaxDepth (int _arg)

void	Train () override

void	Save (const std::string &filename, const std::string &name="") override

void	Load (const std::string &filename, const std::string &name="") override

Classification model file compatibility tests
cv::Ptr< cv::ml::Boost >	m_BoostModel

int	m_BoostType

int	m_WeakCount

double	m_WeightTrimRate

int	m_MaxDepth

bool	CanReadFile (const std::string &) override

bool	CanWriteFile (const std::string &) override

	BoostMachineLearningModel ()

	~BoostMachineLearningModel () override=default

TargetSampleType	DoPredict (const InputSampleType &input, ConfidenceValueType quality=nullptr, ProbaSampleType proba=nullptr) const override

void	PrintSelf (std::ostream &os, itk::Indent indent) const override

	BoostMachineLearningModel (const Self &)=delete

void	operator= (const Self &)=delete

Additional Inherited Members
Public Member Functions inherited from otb::MachineLearningModel< TInputValue, TTargetValue >
virtual const char *	GetNameOfClass () const

TargetSampleType	Predict (const InputSampleType &input, ConfidenceValueType quality=nullptr, ProbaSampleType proba=nullptr) const

virtual void	SetDimension (unsigned int _arg)

virtual unsigned int	GetDimension ()

TargetListSampleType::Pointer	PredictBatch (const InputListSampleType input, ConfidenceListSampleType quality=nullptr, ProbaListSampleType *proba=nullptr) const

bool	HasConfidenceIndex () const

bool	HasProbaIndex () const

virtual void	SetInputListSample (InputListSampleType *_arg)

	itkGetObjectMacro (InputListSample, InputListSampleType)

virtual const InputListSampleType *	GetInputListSample () const

	itkGetObjectMacro (TargetListSample, TargetListSampleType)

	itkGetObjectMacro (ConfidenceListSample, ConfidenceListSampleType)

virtual void	SetTargetListSample (TargetListSampleType *_arg)

virtual bool	GetRegressionMode ()

void	SetRegressionMode (bool flag)

Protected Member Functions inherited from otb::MachineLearningModel< TInputValue, TTargetValue >
	MachineLearningModel ()

	~MachineLearningModel () override=default

void	PrintSelf (std::ostream &os, itk::Indent indent) const override

Protected Attributes inherited from otb::MachineLearningModel< TInputValue, TTargetValue >
InputListSampleType::Pointer	m_InputListSample

InputListSampleType::Pointer	m_ValidationListSample

TargetListSampleType::Pointer	m_TargetListSample

ConfidenceListSampleType::Pointer	m_ConfidenceListSample

bool	m_RegressionMode

bool	m_IsRegressionSupported

bool	m_ConfidenceIndex

bool	m_ProbaIndex

bool	m_IsDoPredictBatchMultiThreaded

unsigned int	m_Dimension

Detailed Description

template<class TInputValue, class TTargetValue>
class otb::BoostMachineLearningModel< TInputValue, TTargetValue >

Definition at line 35 of file otbBoostMachineLearningModel.h.

Member Typedef Documentation

◆ ConfidenceValueType

template<class TInputValue , class TTargetValue >

typedef Superclass::ConfidenceValueType otb::BoostMachineLearningModel< TInputValue, TTargetValue >::ConfidenceValueType

Definition at line 50 of file otbBoostMachineLearningModel.h.

◆ ConstPointer

template<class TInputValue , class TTargetValue >

typedef itk::SmartPointer<const Self> otb::BoostMachineLearningModel< TInputValue, TTargetValue >::ConstPointer

Definition at line 42 of file otbBoostMachineLearningModel.h.

◆ InputListSampleType

template<class TInputValue , class TTargetValue >

typedef Superclass::InputListSampleType otb::BoostMachineLearningModel< TInputValue, TTargetValue >::InputListSampleType

Definition at line 46 of file otbBoostMachineLearningModel.h.

◆ InputSampleType

template<class TInputValue , class TTargetValue >

typedef Superclass::InputSampleType otb::BoostMachineLearningModel< TInputValue, TTargetValue >::InputSampleType

Definition at line 45 of file otbBoostMachineLearningModel.h.

◆ InputValueType

template<class TInputValue , class TTargetValue >

typedef Superclass::InputValueType otb::BoostMachineLearningModel< TInputValue, TTargetValue >::InputValueType

Definition at line 44 of file otbBoostMachineLearningModel.h.

◆ Pointer

template<class TInputValue , class TTargetValue >

typedef itk::SmartPointer<Self> otb::BoostMachineLearningModel< TInputValue, TTargetValue >::Pointer

Definition at line 41 of file otbBoostMachineLearningModel.h.

◆ ProbaSampleType

template<class TInputValue , class TTargetValue >

typedef Superclass::ProbaSampleType otb::BoostMachineLearningModel< TInputValue, TTargetValue >::ProbaSampleType

Definition at line 51 of file otbBoostMachineLearningModel.h.

◆ Self

template<class TInputValue , class TTargetValue >

typedef BoostMachineLearningModel otb::BoostMachineLearningModel< TInputValue, TTargetValue >::Self

Standard class typedefs.

Definition at line 39 of file otbBoostMachineLearningModel.h.

◆ Superclass

template<class TInputValue , class TTargetValue >

typedef MachineLearningModel<TInputValue, TTargetValue> otb::BoostMachineLearningModel< TInputValue, TTargetValue >::Superclass

Definition at line 40 of file otbBoostMachineLearningModel.h.

◆ TargetListSampleType

template<class TInputValue , class TTargetValue >

typedef Superclass::TargetListSampleType otb::BoostMachineLearningModel< TInputValue, TTargetValue >::TargetListSampleType

Definition at line 49 of file otbBoostMachineLearningModel.h.

◆ TargetSampleType

template<class TInputValue , class TTargetValue >

typedef Superclass::TargetSampleType otb::BoostMachineLearningModel< TInputValue, TTargetValue >::TargetSampleType

Definition at line 48 of file otbBoostMachineLearningModel.h.

◆ TargetValueType

template<class TInputValue , class TTargetValue >

typedef Superclass::TargetValueType otb::BoostMachineLearningModel< TInputValue, TTargetValue >::TargetValueType

Definition at line 47 of file otbBoostMachineLearningModel.h.

Constructor & Destructor Documentation

◆ BoostMachineLearningModel() [1/2]

template<class TInputValue , class TOutputValue >

otb::BoostMachineLearningModel< TInputValue, TOutputValue >::BoostMachineLearningModel

protected

Constructor

Definition at line 34 of file otbBoostMachineLearningModel.hxx.

References otb::MachineLearningModel< TInputValue, TTargetValue >::m_ConfidenceIndex.

◆ ~BoostMachineLearningModel()

template<class TInputValue , class TTargetValue >

otb::BoostMachineLearningModel< TInputValue, TTargetValue >::~BoostMachineLearningModel ( )

overrideprotecteddefault

Destructor

◆ BoostMachineLearningModel() [2/2]

template<class TInputValue , class TTargetValue >

otb::BoostMachineLearningModel< TInputValue, TTargetValue >::BoostMachineLearningModel ( const Self & )

privatedelete

Is the input model file readable and compatible with the corresponding classifier ?

Member Function Documentation

◆ CanReadFile()

template<class TInputValue , class TOutputValue >

bool otb::BoostMachineLearningModel< TInputValue, TOutputValue >::CanReadFile ( const std::string & file )

overridevirtual

Is the input model file readable and compatible with the corresponding classifier ?

Implements otb::MachineLearningModel< TInputValue, TTargetValue >.

Definition at line 112 of file otbBoostMachineLearningModel.hxx.

References CV_TYPE_NAME_ML_BOOSTING.

◆ CanWriteFile()

template<class TInputValue , class TOutputValue >

bool otb::BoostMachineLearningModel< TInputValue, TOutputValue >::CanWriteFile ( const std::string & )

overridevirtual

Is the input model file writable and compatible with the corresponding classifier ?

Implements otb::MachineLearningModel< TInputValue, TTargetValue >.

Definition at line 140 of file otbBoostMachineLearningModel.hxx.

◆ CreateAnother()

template<class TInputValue , class TTargetValue >

virtual::itk::LightObject::Pointer otb::BoostMachineLearningModel< TInputValue, TTargetValue >::CreateAnother ( void ) const

Run-time type information (and related methods).

◆ DoPredict()

template<class TInputValue , class TOutputValue >

BoostMachineLearningModel< TInputValue, TOutputValue >::TargetSampleType otb::BoostMachineLearningModel< TInputValue, TOutputValue >::DoPredict	(	const InputSampleType &	input,
		ConfidenceValueType *	quality = `nullptr`,
		ProbaSampleType *	proba = `nullptr`
	)		const

overrideprotected

Predict values using the model

Definition at line 71 of file otbBoostMachineLearningModel.hxx.

◆ GetBoostType()

template<class TInputValue , class TTargetValue >

virtual int otb::BoostMachineLearningModel< TInputValue, TTargetValue >::GetBoostType ( )

virtual

Setters/Getters to the Boost type It can be CvBoost::DISCRETE, CvBoost::REAL, CvBoost::LOGIT, CvBoost::GENTLE Default is CvBoost::REAL.

See also: http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams

◆ GetMaxDepth()

template<class TInputValue , class TTargetValue >

virtual int otb::BoostMachineLearningModel< TInputValue, TTargetValue >::GetMaxDepth ( )

virtual

Setters/Getters to the maximum depth of the tree. Default is 1

See also: http://docs.opencv.org/modules/ml/doc/decision_trees.html#CvDTreeParams::CvDTreeParams%28%29

◆ GetNameOfClass()

template<class TInputValue , class TTargetValue >

virtual const char* otb::BoostMachineLearningModel< TInputValue, TTargetValue >::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods).

◆ GetWeakCount()

template<class TInputValue , class TTargetValue >

virtual int otb::BoostMachineLearningModel< TInputValue, TTargetValue >::GetWeakCount ( )

virtual

Setters/Getters to the number of weak classifiers. Default is 100.

See also: http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams

◆ GetWeightTrimRate()

template<class TInputValue , class TTargetValue >

virtual double otb::BoostMachineLearningModel< TInputValue, TTargetValue >::GetWeightTrimRate ( )

virtual

Setters/Getters to the threshold WeightTrimRate. A threshold between 0 and 1 used to save computational time. Samples with summary weight $w \leq 1 - WeightTrimRate$ do not participate in the next iteration of training. Set this parameter to 0 to turn off this functionality. Default is 0.95

See also: http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams

◆ Load()

template<class TInputValue , class TOutputValue >

void otb::BoostMachineLearningModel< TInputValue, TOutputValue >::Load	(	const std::string &	filename,
		const std::string &	name = `""`
	)

overridevirtual

Load the model from file

Implements otb::MachineLearningModel< TInputValue, TTargetValue >.

Definition at line 105 of file otbBoostMachineLearningModel.hxx.

◆ New()

template<class TInputValue , class TTargetValue >

static Pointer otb::BoostMachineLearningModel< TInputValue, TTargetValue >::New ( )

static

Run-time type information (and related methods).

◆ operator=()

template<class TInputValue , class TTargetValue >

void otb::BoostMachineLearningModel< TInputValue, TTargetValue >::operator= ( const Self & )

privatedelete

Is the input model file readable and compatible with the corresponding classifier ?

◆ PrintSelf()

template<class TInputValue , class TOutputValue >

void otb::BoostMachineLearningModel< TInputValue, TOutputValue >::PrintSelf	(	std::ostream &	os,
		itk::Indent	indent
	)		const

overrideprotected

PrintSelf method

Definition at line 146 of file otbBoostMachineLearningModel.hxx.

◆ Save()

template<class TInputValue , class TOutputValue >

void otb::BoostMachineLearningModel< TInputValue, TOutputValue >::Save	(	const std::string &	filename,
		const std::string &	name = `""`
	)

overridevirtual

Save the model to file

Implements otb::MachineLearningModel< TInputValue, TTargetValue >.

Definition at line 95 of file otbBoostMachineLearningModel.hxx.

◆ SetBoostType()

template<class TInputValue , class TTargetValue >

virtual void otb::BoostMachineLearningModel< TInputValue, TTargetValue >::SetBoostType ( int _arg )

virtual

Run-time type information (and related methods).

◆ SetMaxDepth()

template<class TInputValue , class TTargetValue >

virtual void otb::BoostMachineLearningModel< TInputValue, TTargetValue >::SetMaxDepth ( int _arg )

virtual

Run-time type information (and related methods).

◆ SetWeakCount()

template<class TInputValue , class TTargetValue >

virtual void otb::BoostMachineLearningModel< TInputValue, TTargetValue >::SetWeakCount ( int _arg )

virtual

Run-time type information (and related methods).

◆ SetWeightTrimRate()

template<class TInputValue , class TTargetValue >

virtual void otb::BoostMachineLearningModel< TInputValue, TTargetValue >::SetWeightTrimRate ( double _arg )

virtual

Run-time type information (and related methods).

◆ Train()

template<class TInputValue , class TOutputValue >

void otb::BoostMachineLearningModel< TInputValue, TOutputValue >::Train

overridevirtual

Train the machine learning model

Implements otb::MachineLearningModel< TInputValue, TTargetValue >.

Definition at line 46 of file otbBoostMachineLearningModel.hxx.

References CV_VAR_CATEGORICAL, and CV_VAR_NUMERICAL.

Member Data Documentation

◆ m_BoostModel

template<class TInputValue , class TTargetValue >

cv::Ptr<cv::ml::Boost> otb::BoostMachineLearningModel< TInputValue, TTargetValue >::m_BoostModel

private

Is the input model file readable and compatible with the corresponding classifier ?

Definition at line 129 of file otbBoostMachineLearningModel.h.

◆ m_BoostType

template<class TInputValue , class TTargetValue >

int otb::BoostMachineLearningModel< TInputValue, TTargetValue >::m_BoostType

private

Is the input model file readable and compatible with the corresponding classifier ?

Definition at line 131 of file otbBoostMachineLearningModel.h.

◆ m_MaxDepth

template<class TInputValue , class TTargetValue >

int otb::BoostMachineLearningModel< TInputValue, TTargetValue >::m_MaxDepth

private

Is the input model file readable and compatible with the corresponding classifier ?

Definition at line 134 of file otbBoostMachineLearningModel.h.

◆ m_WeakCount

template<class TInputValue , class TTargetValue >

int otb::BoostMachineLearningModel< TInputValue, TTargetValue >::m_WeakCount

private

Is the input model file readable and compatible with the corresponding classifier ?

Definition at line 132 of file otbBoostMachineLearningModel.h.

◆ m_WeightTrimRate

template<class TInputValue , class TTargetValue >

double otb::BoostMachineLearningModel< TInputValue, TTargetValue >::m_WeightTrimRate

private

Is the input model file readable and compatible with the corresponding classifier ?

Definition at line 133 of file otbBoostMachineLearningModel.h.

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

Public Types

Classification model file compatibility tests

Additional Inherited Members

Detailed Description

template<class TInputValue, class TTargetValue> class otb::BoostMachineLearningModel< TInputValue, TTargetValue >

Member Typedef Documentation

◆ ConfidenceValueType

◆ ConstPointer

◆ InputListSampleType

◆ InputSampleType

◆ InputValueType

◆ Pointer

◆ ProbaSampleType

◆ Self

◆ Superclass

◆ TargetListSampleType

◆ TargetSampleType

◆ TargetValueType

Constructor & Destructor Documentation

◆ BoostMachineLearningModel() [1/2]

◆ ~BoostMachineLearningModel()

◆ BoostMachineLearningModel() [2/2]

Member Function Documentation

◆ CanReadFile()

◆ CanWriteFile()

◆ CreateAnother()

◆ DoPredict()

◆ GetBoostType()

◆ GetMaxDepth()

◆ GetNameOfClass()

◆ GetWeakCount()

◆ GetWeightTrimRate()

◆ Load()

◆ New()

◆ operator=()

◆ PrintSelf()

◆ Save()

◆ SetBoostType()

◆ SetMaxDepth()

◆ SetWeakCount()

◆ SetWeightTrimRate()

◆ Train()

Member Data Documentation

◆ m_BoostModel

◆ m_BoostType

◆ m_MaxDepth

◆ m_WeakCount

◆ m_WeightTrimRate

template<class TInputValue, class TTargetValue>
class otb::BoostMachineLearningModel< TInputValue, TTargetValue >