OTB  9.0.0
Orfeo Toolbox
Public Types | List of all members
otb::SVMMachineLearningModel< TInputValue, TTargetValue > Class Template Reference

#include <otbSVMMachineLearningModel.h>

+ Inheritance diagram for otb::SVMMachineLearningModel< TInputValue, TTargetValue >:
+ Collaboration diagram for otb::SVMMachineLearningModel< TInputValue, TTargetValue >:

Public Types

typedef Superclass::ConfidenceValueType ConfidenceValueType
 
typedef itk::SmartPointer< const SelfConstPointer
 
typedef Superclass::InputListSampleType InputListSampleType
 
typedef Superclass::InputSampleType InputSampleType
 
typedef Superclass::InputValueType InputValueType
 
typedef itk::SmartPointer< SelfPointer
 
typedef Superclass::ProbaSampleType ProbaSampleType
 
typedef SVMMachineLearningModel 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< SelfPointer
 
typedef itk::SmartPointer< const SelfConstPointer
 
typedef MLMSampleTraits< TInputValue >::ValueType InputValueType
 
typedef MLMSampleTraits< TInputValue >::SampleType InputSampleType
 
typedef itk::Statistics::ListSample< InputSampleTypeInputListSampleType
 
typedef MLMTargetTraits< TTargetValue >::ValueType TargetValueType
 
typedef MLMTargetTraits< TTargetValue >::SampleType TargetSampleType
 
typedef itk::Statistics::ListSample< TargetSampleTypeTargetListSampleType
 
typedef MLMTargetTraits< double >::ValueType ConfidenceValueType
 
typedef MLMTargetTraits< double >::SampleType ConfidenceSampleType
 
typedef itk::Statistics::ListSample< ConfidenceSampleTypeConfidenceListSampleType
 
typedef itk::VariableLengthVector< double > ProbaSampleType
 
typedef itk::Statistics::ListSample< ProbaSampleTypeProbaListSampleType
 
static Pointer New ()
 
virtual ::itk::LightObject::Pointer CreateAnother (void) const
 
virtual const char * GetNameOfClass () const
 
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::SVM > m_SVMModel
 
int m_SVMType
 
int m_KernelType
 
double m_Degree
 
double m_Gamma
 
double m_Coef0
 
double m_C
 
double m_Nu
 
double m_P
 
int m_TermCriteriaType
 
int m_MaxIter
 
double m_Epsilon
 
bool m_ParameterOptimization
 
double m_OutputDegree
 
double m_OutputGamma
 
double m_OutputCoef0
 
double m_OutputC
 
double m_OutputNu
 
double m_OutputP
 
bool CanReadFile (const std::string &) override
 
bool CanWriteFile (const std::string &) override
 
virtual int GetSVMType ()
 
virtual void SetSVMType (int _arg)
 
virtual int GetKernelType ()
 
virtual void SetKernelType (int _arg)
 
virtual int GetTermCriteriaType ()
 
virtual void SetTermCriteriaType (int _arg)
 
virtual int GetMaxIter ()
 
virtual void SetMaxIter (int _arg)
 
virtual double GetEpsilon ()
 
virtual void SetEpsilon (double _arg)
 
virtual double GetDegree ()
 
virtual void SetDegree (double _arg)
 
virtual double GetOutputDegree ()
 
virtual double GetGamma ()
 
virtual void SetGamma (double _arg)
 
virtual double GetOutputGamma ()
 
virtual double GetCoef0 ()
 
virtual void SetCoef0 (double _arg)
 
virtual double GetOutputCoef0 ()
 
virtual double GetC ()
 
virtual void SetC (double _arg)
 
virtual double GetOutputC ()
 
virtual double GetNu ()
 
virtual void SetNu (double _arg)
 
virtual double GetOutputNu ()
 
virtual double GetP ()
 
virtual void SetP (double _arg)
 
virtual double GetOutputP ()
 
virtual bool GetParameterOptimization ()
 
virtual void SetParameterOptimization (bool _arg)
 
 SVMMachineLearningModel ()
 
 ~SVMMachineLearningModel () 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
 
 SVMMachineLearningModel (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 InputListSampleTypeGetInputListSample () 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::SVMMachineLearningModel< TInputValue, TTargetValue >

OpenCV implementation of SVM algorithm.

This machine learning model uses the OpenCV implementation of the SVM algorithm. Since this implementation is buggy in the linear case, we recommend users to use the LibSVM implementation instead, through the otb::LibSVMMachineLearningModel.

Definition at line 42 of file otbSVMMachineLearningModel.h.

Member Typedef Documentation

◆ ConfidenceValueType

template<class TInputValue , class TTargetValue >
typedef Superclass::ConfidenceValueType otb::SVMMachineLearningModel< TInputValue, TTargetValue >::ConfidenceValueType

Definition at line 58 of file otbSVMMachineLearningModel.h.

◆ ConstPointer

template<class TInputValue , class TTargetValue >
typedef itk::SmartPointer<const Self> otb::SVMMachineLearningModel< TInputValue, TTargetValue >::ConstPointer

Definition at line 50 of file otbSVMMachineLearningModel.h.

◆ InputListSampleType

template<class TInputValue , class TTargetValue >
typedef Superclass::InputListSampleType otb::SVMMachineLearningModel< TInputValue, TTargetValue >::InputListSampleType

Definition at line 54 of file otbSVMMachineLearningModel.h.

◆ InputSampleType

template<class TInputValue , class TTargetValue >
typedef Superclass::InputSampleType otb::SVMMachineLearningModel< TInputValue, TTargetValue >::InputSampleType

Definition at line 53 of file otbSVMMachineLearningModel.h.

◆ InputValueType

template<class TInputValue , class TTargetValue >
typedef Superclass::InputValueType otb::SVMMachineLearningModel< TInputValue, TTargetValue >::InputValueType

Definition at line 52 of file otbSVMMachineLearningModel.h.

◆ Pointer

template<class TInputValue , class TTargetValue >
typedef itk::SmartPointer<Self> otb::SVMMachineLearningModel< TInputValue, TTargetValue >::Pointer

Definition at line 49 of file otbSVMMachineLearningModel.h.

◆ ProbaSampleType

template<class TInputValue , class TTargetValue >
typedef Superclass::ProbaSampleType otb::SVMMachineLearningModel< TInputValue, TTargetValue >::ProbaSampleType

Definition at line 59 of file otbSVMMachineLearningModel.h.

◆ Self

template<class TInputValue , class TTargetValue >
typedef SVMMachineLearningModel otb::SVMMachineLearningModel< TInputValue, TTargetValue >::Self

Standard class typedefs.

Definition at line 47 of file otbSVMMachineLearningModel.h.

◆ Superclass

template<class TInputValue , class TTargetValue >
typedef MachineLearningModel<TInputValue, TTargetValue> otb::SVMMachineLearningModel< TInputValue, TTargetValue >::Superclass

Definition at line 48 of file otbSVMMachineLearningModel.h.

◆ TargetListSampleType

template<class TInputValue , class TTargetValue >
typedef Superclass::TargetListSampleType otb::SVMMachineLearningModel< TInputValue, TTargetValue >::TargetListSampleType

Definition at line 57 of file otbSVMMachineLearningModel.h.

◆ TargetSampleType

template<class TInputValue , class TTargetValue >
typedef Superclass::TargetSampleType otb::SVMMachineLearningModel< TInputValue, TTargetValue >::TargetSampleType

Definition at line 56 of file otbSVMMachineLearningModel.h.

◆ TargetValueType

template<class TInputValue , class TTargetValue >
typedef Superclass::TargetValueType otb::SVMMachineLearningModel< TInputValue, TTargetValue >::TargetValueType

Definition at line 55 of file otbSVMMachineLearningModel.h.

Constructor & Destructor Documentation

◆ SVMMachineLearningModel() [1/2]

template<class TInputValue , class TOutputValue >
otb::SVMMachineLearningModel< TInputValue, TOutputValue >::SVMMachineLearningModel
protected

◆ ~SVMMachineLearningModel()

template<class TInputValue , class TTargetValue >
otb::SVMMachineLearningModel< TInputValue, TTargetValue >::~SVMMachineLearningModel ( )
overrideprotecteddefault

Destructor

◆ SVMMachineLearningModel() [2/2]

template<class TInputValue , class TTargetValue >
otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SVMMachineLearningModel ( 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::SVMMachineLearningModel< 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 154 of file otbSVMMachineLearningModel.hxx.

References CV_TYPE_NAME_ML_SVM.

◆ CanWriteFile()

template<class TInputValue , class TOutputValue >
bool otb::SVMMachineLearningModel< 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 181 of file otbSVMMachineLearningModel.hxx.

◆ CreateAnother()

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

Run-time type information (and related methods).

◆ DoPredict()

template<class TInputValue , class TOutputValue >
SVMMachineLearningModel< TInputValue, TOutputValue >::TargetSampleType otb::SVMMachineLearningModel< TInputValue, TOutputValue >::DoPredict ( const InputSampleType input,
ConfidenceValueType quality = nullptr,
ProbaSampleType proba = nullptr 
) const
overrideprotected

Predict values using the model

Definition at line 114 of file otbSVMMachineLearningModel.hxx.

◆ GetC()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetC ( )
virtual

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

◆ GetCoef0()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetCoef0 ( )
virtual

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

◆ GetDegree()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetDegree ( )
virtual

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

◆ GetEpsilon()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetEpsilon ( )
virtual

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

◆ GetGamma()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetGamma ( )
virtual

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

◆ GetKernelType()

template<class TInputValue , class TTargetValue >
virtual int otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetKernelType ( )
virtual

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

◆ GetMaxIter()

template<class TInputValue , class TTargetValue >
virtual int otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetMaxIter ( )
virtual

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

◆ GetNameOfClass()

template<class TInputValue , class TTargetValue >
virtual const char* otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetNameOfClass ( ) const
virtual

Run-time type information (and related methods).

◆ GetNu()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetNu ( )
virtual

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

◆ GetOutputC()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetOutputC ( )
virtual

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

◆ GetOutputCoef0()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetOutputCoef0 ( )
virtual

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

◆ GetOutputDegree()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetOutputDegree ( )
virtual

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

◆ GetOutputGamma()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetOutputGamma ( )
virtual

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

◆ GetOutputNu()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetOutputNu ( )
virtual

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

◆ GetOutputP()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetOutputP ( )
virtual

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

◆ GetP()

template<class TInputValue , class TTargetValue >
virtual double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetP ( )
virtual

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

◆ GetParameterOptimization()

template<class TInputValue , class TTargetValue >
virtual bool otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetParameterOptimization ( )
virtual

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

◆ GetSVMType()

template<class TInputValue , class TTargetValue >
virtual int otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetSVMType ( )
virtual

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

◆ GetTermCriteriaType()

template<class TInputValue , class TTargetValue >
virtual int otb::SVMMachineLearningModel< TInputValue, TTargetValue >::GetTermCriteriaType ( )
virtual

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

◆ Load()

template<class TInputValue , class TOutputValue >
void otb::SVMMachineLearningModel< 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 147 of file otbSVMMachineLearningModel.hxx.

◆ New()

template<class TInputValue , class TTargetValue >
static Pointer otb::SVMMachineLearningModel< TInputValue, TTargetValue >::New ( )
static

Run-time type information (and related methods).

◆ operator=()

template<class TInputValue , class TTargetValue >
void otb::SVMMachineLearningModel< 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::SVMMachineLearningModel< TInputValue, TOutputValue >::PrintSelf ( std::ostream &  os,
itk::Indent  indent 
) const
overrideprotected

PrintSelf method

Definition at line 187 of file otbSVMMachineLearningModel.hxx.

◆ Save()

template<class TInputValue , class TOutputValue >
void otb::SVMMachineLearningModel< 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 137 of file otbSVMMachineLearningModel.hxx.

◆ SetC()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetC ( double  _arg)
virtual

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

◆ SetCoef0()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetCoef0 ( double  _arg)
virtual

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

◆ SetDegree()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetDegree ( double  _arg)
virtual

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

◆ SetEpsilon()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetEpsilon ( double  _arg)
virtual

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

◆ SetGamma()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetGamma ( double  _arg)
virtual

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

◆ SetKernelType()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetKernelType ( int  _arg)
virtual

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

◆ SetMaxIter()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetMaxIter ( int  _arg)
virtual

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

◆ SetNu()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetNu ( double  _arg)
virtual

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

◆ SetP()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetP ( double  _arg)
virtual

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

◆ SetParameterOptimization()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetParameterOptimization ( bool  _arg)
virtual

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

◆ SetSVMType()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetSVMType ( int  _arg)
virtual

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

◆ SetTermCriteriaType()

template<class TInputValue , class TTargetValue >
virtual void otb::SVMMachineLearningModel< TInputValue, TTargetValue >::SetTermCriteriaType ( int  _arg)
virtual

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

◆ Train()

template<class TInputValue , class TOutputValue >
void otb::SVMMachineLearningModel< TInputValue, TOutputValue >::Train
overridevirtual

Train the machine learning model

Implements otb::MachineLearningModel< TInputValue, TTargetValue >.

Definition at line 61 of file otbSVMMachineLearningModel.hxx.

References CV_VAR_CATEGORICAL, and CV_VAR_NUMERICAL.

Member Data Documentation

◆ m_C

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_C
private

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

Definition at line 156 of file otbSVMMachineLearningModel.h.

◆ m_Coef0

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_Coef0
private

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

Definition at line 155 of file otbSVMMachineLearningModel.h.

◆ m_Degree

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_Degree
private

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

Definition at line 153 of file otbSVMMachineLearningModel.h.

◆ m_Epsilon

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_Epsilon
private

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

Definition at line 161 of file otbSVMMachineLearningModel.h.

◆ m_Gamma

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_Gamma
private

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

Definition at line 154 of file otbSVMMachineLearningModel.h.

◆ m_KernelType

template<class TInputValue , class TTargetValue >
int otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_KernelType
private

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

Definition at line 152 of file otbSVMMachineLearningModel.h.

◆ m_MaxIter

template<class TInputValue , class TTargetValue >
int otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_MaxIter
private

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

Definition at line 160 of file otbSVMMachineLearningModel.h.

◆ m_Nu

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_Nu
private

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

Definition at line 157 of file otbSVMMachineLearningModel.h.

◆ m_OutputC

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_OutputC
private

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

Definition at line 167 of file otbSVMMachineLearningModel.h.

◆ m_OutputCoef0

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_OutputCoef0
private

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

Definition at line 166 of file otbSVMMachineLearningModel.h.

◆ m_OutputDegree

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_OutputDegree
private

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

Definition at line 164 of file otbSVMMachineLearningModel.h.

◆ m_OutputGamma

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_OutputGamma
private

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

Definition at line 165 of file otbSVMMachineLearningModel.h.

◆ m_OutputNu

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_OutputNu
private

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

Definition at line 168 of file otbSVMMachineLearningModel.h.

◆ m_OutputP

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_OutputP
private

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

Definition at line 169 of file otbSVMMachineLearningModel.h.

◆ m_P

template<class TInputValue , class TTargetValue >
double otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_P
private

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

Definition at line 158 of file otbSVMMachineLearningModel.h.

◆ m_ParameterOptimization

template<class TInputValue , class TTargetValue >
bool otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_ParameterOptimization
private

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

Definition at line 162 of file otbSVMMachineLearningModel.h.

◆ m_SVMModel

template<class TInputValue , class TTargetValue >
cv::Ptr<cv::ml::SVM> otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_SVMModel
private

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

Definition at line 150 of file otbSVMMachineLearningModel.h.

◆ m_SVMType

template<class TInputValue , class TTargetValue >
int otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_SVMType
private

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

Definition at line 151 of file otbSVMMachineLearningModel.h.

◆ m_TermCriteriaType

template<class TInputValue , class TTargetValue >
int otb::SVMMachineLearningModel< TInputValue, TTargetValue >::m_TermCriteriaType
private

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

Definition at line 159 of file otbSVMMachineLearningModel.h.


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