source: branches/0.4-stable/yat/classifier/GaussianKernelFunction.h @ 1392

#ifndef _theplu_yat_classifier_gaussian_kernel_function_
#define _theplu_yat_classifier_gaussian_kernel_function_

// $Id$

/*
  Copyright (C) 2004, 2005, 2006, 2007 Jari Häkkinen, Peter Johansson

  This file is part of the yat library, http://dev.thep.lu.se/yat

  The yat library is free software; you can redistribute it and/or
  modify it under the terms of the GNU General Public License as
  published by the Free Software Foundation; either version 2 of the
  License, or (at your option) any later version.

  The yat library is distributed in the hope that it will be useful,
  but WITHOUT ANY WARRANTY; without even the implied warranty of
  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
  General Public License for more details.

  You should have received a copy of the GNU General Public License
  along with this program; if not, write to the Free Software
  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
  02111-1307, USA.
*/

#include "KernelFunction.h"

#include <cmath>

namespace theplu {
namespace yat {
namespace classifier {

  class DataLookup1D;

  ///
  /// @brief Class for Gaussian kernel calculations.
  ///
 
  class GaussianKernelFunction : public KernelFunction 
  {
    
  public:
    ///
    /// Constructor taking the sigma_ , i.e. the width of the Gaussian,as
    /// input. Default is sigma_ = 1.
    ///
    GaussianKernelFunction(double = 1);
    
    ///
    ///Destructor
    ///
       virtual ~GaussianKernelFunction(void) {};
    
    ///
    /// returning the scalar product of two vectors in feature space using the
    /// Gaussian kernel. @return \f$ exp(-(x - y)^{2}/\sigma^2) \f$ \n
    ///
    double operator()(const DataLookup1D& x,
                      const DataLookup1D& y) const; 

    /**
       \f$ \exp(-d^2/\sigma^2) \f$ where \f$ d^2 = \sum w_y(x_i-y_i)^2
       / \sum w_y * N \f$
     **/
    double operator()(const DataLookup1D& x,
                      const DataLookupWeighted1D& y) const; 

    /**
       \f$ \exp(-d^2/\sigma^2) \f$ where \f$ d^2 = \sum w_xw_y(x_i-y_i)^2
       / \sum w_xw_y * N \f$
     **/
    double operator()(const DataLookupWeighted1D& x,
                      const DataLookupWeighted1D& y) const; 

  private:
    double sigma2_;

  }; // class GaussianKernelFunction

}}} // of namespace classifier, yat, and theplu

#endif