source: trunk/lib/classifier/Kernel_SEV.h @ 542

// $Id: Kernel_SEV.h 542 2006-03-05 15:46:47Z peter $

#ifndef _theplu_classifier_kernel_sev_
#define _theplu_classifier_kernel_sev_

#include <c++_tools/classifier/Kernel.h>
#include <c++_tools/gslapi/matrix.h>


namespace theplu {
namespace classifier {

  class DataLookup1D;
  class KernelFunction;

  ///
  ///   @brief Speed 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 Speed Efficient Version (SEV) calculated
  ///   the kernel matrix once and the kernel is stored in
  ///   memory. When \f$N\f$ is large and the kernel matrix cannot be
  ///   stored in memory, use Kernel_MEV instead.
  ///   
  ///   @see also Kernel_MEV
  ///
  class Kernel_SEV : public Kernel 
  {
    
  public:

    ///
    ///  Default constructor (not implemented)
    ///
    Kernel_SEV(void);

    ///
    ///   Constructor taking the data matrix and KernelFunction as
    ///   input. @note Can not handle NaNs. When dealing with missing values,
    ///   use constructor taking a weight matrix.
    Kernel_SEV(const MatrixLookup&, const KernelFunction&);
    
    ///
    /// Copy constructor (not implemented)
    ///
    Kernel_SEV(const Kernel_SEV&);

    ///
    ///   Destructor
    ///
    inline virtual ~Kernel_SEV(void) {};

    ///
    /// @return element at position (\a row, \a column) in the Kernel
    /// matrix
    ///
    inline double operator()(const size_t row,const size_t column) const
    { return kernel_matrix_(row,column); }

    ///
    /// @return kernel element between data @a ve and training sample @a i
    /// 
    double element(const DataLookup1D& vec, const size_t i) const;
    double element(const DataLookup1D& vec, const DataLookup1D& w, 
                   const size_t i) const;


  private:
    gslapi::matrix kernel_matrix_;

  }; // class Kernel_SEV

}} // of namespace classifier and namespace theplu

#endif