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- /**
- * @file KCGPLaplace.h
- * @brief Gaussian Process Regression for Classification
- * @author Erik Rodner
- * @date 12/03/2009
- */
- #ifndef KCGPLAPLACEINCLUDE
- #define KCGPLAPLACEINCLUDE
- #include "vislearning/classifier/classifierbase/KernelClassifier.h"
- #include "vislearning/math/kernels/ParameterizedKernel.h"
- #include "vislearning/classifier/kernelclassifier/LaplaceApproximation.h"
- #include "vislearning/classifier/kernelclassifier/LikelihoodFunction.h"
- #undef ROADWORKS
- #define ROADWORKS fthrow(Exception, "Persistent interface not implemented!");
- namespace OBJREC {
-
- /** Gaussian Process Regression for Classification */
- class KCGPLaplace : public KernelClassifier
- {
- protected:
-
- enum {
- OPTIMIZATION_METHOD_RASMUSSEN = 0,
- OPTIMIZATION_METHOD_TRUSTREGION
- };
- int optimizationMethod;
- bool verbose;
- bool optimizeParameters;
- NICE::Vector y;
- LaplaceApproximation laplaceApproximation;
- LikelihoodFunction *likelihoodFunction;
- public:
-
- /** simple constructor */
- KCGPLaplace( const NICE::Config *conf, Kernel *kernel = NULL, const std::string & section = "KCGPLaplace" );
- /** copy constructor */
- KCGPLaplace( const KCGPLaplace & src );
-
- /** simple destructor */
- virtual ~KCGPLaplace();
-
- /** teach the classifier with a kernel matrix and the corresponding class labels @param y ! */
- void teach ( KernelData *kernelData, const NICE::Vector & y );
-
- /** classify an example by using its kernel values with the training set,
- be careful with the order in @param kernelVector */
- virtual ClassificationResult classifyKernel ( const NICE::Vector & kernelVector, double kernelSelf ) const;
-
- /** clone this object */
- KCGPLaplace *clone() const;
- void restore(std::istream&, int) { ROADWORKS };
- void store(std::ostream&, int) const { ROADWORKS };
- void clear() { ROADWORKS };
- };
- }
- #undef ROADWORKS
- #endif
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