NICE_VisLearning/regression/regressionbase/RegressionAlgorithmKernel.h

/** 
* @file RegressionAlgorithmKernel.h
* @brief interface for a regression algorithm which is based on kernels
* @author Erik Rodner
* @date 12/09/2009

*/
#ifndef REGRESSIONALGORITHMKERNELINCLUDE
#define REGRESSIONALGORITHMKERNELINCLUDE

#include "vislearning/math/kernels/Kernel.h"
#include "vislearning/math/kernels/KernelData.h"
#include "RegressionAlgorithm.h"

namespace OBJREC {
  
/** interface for a regression algorithm which is based on kernels */
class RegressionAlgorithmKernel : public RegressionAlgorithm
{
    protected:
		NICE::VVector X;
		NICE::Vector y;

		NICE::Config conf;

		Kernel *kernelFunction;

    public:
  
		/** simple constructor */
		RegressionAlgorithmKernel( const NICE::Config *conf, Kernel *kernelFunction = NULL );

		/** copy constructor */
		RegressionAlgorithmKernel( const RegressionAlgorithmKernel & src );
		  
		/** simple destructor */
		virtual ~RegressionAlgorithmKernel();
		 
		/** learn parameters/models/whatever with a kernel matrix (contained in a general structure kernel data)
		 *  of a set
		 *  of vectors and the corresponding function values \c y 
		 */
		virtual void teach ( KernelData *kernelData, const NICE::Vector & y ) = 0;

		/** predict the function value for a vector by using its kernel values with
		 * the used training set, be careful with the order in \c kernelVector
		 */
		virtual double predictKernel ( const NICE::Vector & kernelVector, double kernelSelf ) = 0;
		
		// functions to build an interface to RegressionAlgorithm
		
		/** learn parameters/models/whatever using a set of vectors and
		 *  their corresponding function values
		 */
		void teach ( const NICE::VVector & X, const NICE::Vector & y ); 

		/** predict the function value for \c x */
		double predict ( const NICE::Vector & x );

		/** clone function */
		virtual RegressionAlgorithmKernel *clone(void) const {
			fthrow(Exception, "clone() not yet implemented!\n");
		}

};

}

#endif