source: trunk/yat/classifier/Kernel_MEV.h @ 1275

#ifndef _theplu_yat_classifier_kernel_mev_
#define _theplu_yat_classifier_kernel_mev_

// $Id$

/*
  Copyright (C) 2003 Peter Johansson
  Copyright (C) 2004, 2005 Jari Häkkinen, Peter Johansson
  Copyright (C) 2006 Jari Häkkinen, Peter Johansson, Markus Ringnér
  Copyright (C) 2007 Jari Häkkinen, Peter Johansson
  Copyright (C) 2008 Peter Johansson

  This file is part of the yat library, http://trac.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 "Kernel.h"
#include "KernelFunction.h"

namespace theplu {
namespace yat {
namespace classifier {
  class MatrixLookup;
  class MatrixLookupWeighted;

  ///
  /// @brief Memory Efficient Kernel 
  ///
  ///   Class taking care of the
  ///   \f$ NxN \f$ kernel matrix, where \f$ N \f$ is number of
  ///   samples. Type of Kernel is defined by a KernelFunction. This
  ///   Memory Efficient Version (MEV) does not store the kernel
  ///   matrix in memory, but calculates an element when it is
  ///   needed. When memory allows do always use Kernel_SEV
  ///   instead. 
  ///
  class Kernel_MEV : public Kernel 
  {
    
  public:
    
    ///
    /// Constructor taking the data matrix and KernelFunction as
    /// input. Each column in the data matrix corresponds to one
    /// sample. @note Can not handle NaNs. 
    ///
    Kernel_MEV(const MatrixLookup& data, const KernelFunction& kf, 
               const bool own=false);


    ///
    /// Constructor taking the data matrix and KernelFunction as
    /// input. Each column in the data matrix corresponds to one
    /// sample. @note Can not handle NaNs. 
    ///
    Kernel_MEV(const MatrixLookupWeighted& data, const KernelFunction& kf,
               const bool own=false);


    ///
    /// Constructing a new Kernel based on selected features @a
    /// index. All other seeting are the same.
    ///
    Kernel_MEV(const Kernel_MEV& kernel, const std::vector<size_t>& index);


    ///
    /// @return Element at position (\a row, \a column) of the Kernel
    /// matrix
    ///
    double operator()(const size_t row, const size_t column) const;
    
    ///
    /// An interface for making new classifier objects. This function
    /// allows for specification at run-time of which kernel to
    /// instatiate (see 'Prototype' in Design Patterns).
    ///
    /// @note Returns a dynamically allocated Kernel, which has
    /// to be deleted by the caller to avoid memory leaks.
    ///
    const Kernel_MEV* make_kernel(const MatrixLookup&, 
                                  const bool own=false) const;


    ///
    /// An interface for making new classifier objects. This function
    /// allows for specification at run-time of which kernel to
    /// instatiate (see 'Prototype' in Design Patterns).
    ///
    /// @note Returns a dynamically allocated Kernel, which has
    /// to be deleted by the caller to avoid memory leaks.
    ///
    const Kernel_MEV* make_kernel(const MatrixLookupWeighted&, 
                                  const bool own=false) const;


  private:
    ///
    /// Copy constructor (not implemented)
    ///
    Kernel_MEV(const Kernel_MEV&);
    const Kernel_MEV& operator=(const Kernel_MEV&);

  }; // class Kernel_MEV

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

#endif