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#ifndef PCAModel_h
#define PCAModel_h
#include "DimensionalityReductionModel.h"
#include <shark/Algorithms/Trainers/PCA.h>
namespace otb
{
template <class TInputValue>
class ITK_EXPORT PCAModel: public DimensionalityReductionModel<TInputValue,TInputValue>
{
public:
typedef PCAModel Self;
typedef DimensionalityReductionModel<TInputValue,TInputValue> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
typedef typename Superclass::InputValueType InputValueType;
typedef typename Superclass::InputSampleType InputSampleType;
typedef typename Superclass::InputListSampleType InputListSampleType;
typedef typename Superclass::TargetValueType TargetValueType;
typedef typename Superclass::TargetSampleType TargetSampleType;
typedef typename Superclass::TargetListSampleType TargetListSampleType;
typedef typename Superclass::ConfidenceValueType ConfidenceValueType;
typedef typename Superclass::ConfidenceSampleType ConfidenceSampleType;
typedef typename Superclass::ConfidenceListSampleType ConfidenceListSampleType;
itkNewMacro(Self);
itkTypeMacro(AutoencoderModel, DimensionalityReductionModel);
unsigned int GetDimension() {return m_Dimension;};
Cédric Traizet
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itkSetMacro(Dimension,unsigned int);
bool CanReadFile(const std::string & filename);
bool CanWriteFile(const std::string & filename);
void Save(const std::string & filename, const std::string & name="") ITK_OVERRIDE;
void Load(const std::string & filename, const std::string & name="") ITK_OVERRIDE;
void Train() ITK_OVERRIDE;
//void Dimensionality_reduction() {}; // Dimensionality reduction is done by DoPredict
protected:
PCAModel();
~PCAModel() ITK_OVERRIDE;
virtual TargetSampleType DoPredict(const InputSampleType& input, ConfidenceValueType *quality=ITK_NULLPTR) const ITK_OVERRIDE;
virtual void DoPredictBatch(const InputListSampleType *, const unsigned int & startIndex, const unsigned int & size, TargetListSampleType *, ConfidenceListSampleType * = ITK_NULLPTR) const ITK_OVERRIDE;
private:
shark::LinearModel<> m_encoder;
shark::LinearModel<> m_decoder;
shark::PCA m_pca;