Ignore:
Timestamp:
Aug 24, 2006, 1:18:28 PM (15 years ago)
Author:
Peter
Message:

added random_shuffle function in Target class

File:
1 edited

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Unmodified
Added
Removed
  • trunk/c++_tools/classifier/Kernel_SEV.h

    r555 r592  
    1414  class KernelFunction;
    1515
    16   ///
     16  ///
    1717  ///   @brief Speed Efficient Kernel
    18   ///   Class taking care of the \f$NxN\f$ kernel matrix, where
    19   ///   \f$N\f$ is number of samples. Type of Kernel is defined by a
    20   ///   KernelFunction. This Speed Efficient Version (SEV) calculated
    21   ///   the kernel matrix once and the kernel is stored in
    22   ///   memory. When \f$N\f$ is large and the kernel matrix cannot be
    23   ///   stored in memory, use Kernel_MEV instead.
    24   ///   
    25   ///   @see also Kernel_MEV
    26   ///
     18  ///   Class taking care of the \f$NxN\f$ kernel matrix, where
     19  ///   \f$N\f$ is number of samples. Type of Kernel is defined by a
     20  ///   KernelFunction. This Speed Efficient Version (SEV) calculated
     21  ///   the kernel matrix once by construction and the kernel is stored in
     22  ///   memory. When \f$N\f$ is large and the kernel matrix cannot be
     23  ///   stored in memory, use Kernel_MEV instead.
     24  ///   
     25  ///   @see also Kernel_MEV KernelWeighted_SEV
     26  ///
    2727  class Kernel_SEV : public Kernel
    2828  {
     
    3131
    3232    ///
    33     ///   Constructor taking the data matrix and KernelFunction as
    34     ///   input. @note Can not handle NaNs. When dealing with missing values,
    35     ///   use constructor taking a weight matrix.
     33    /// Constructor taking the data matrix and KernelFunction as
     34    /// input. @note Can not handle NaNs. When dealing with missing values,
     35    /// use KernelWeighted_SEV instead.
     36    ///
    3637    Kernel_SEV(const MatrixLookup&, const KernelFunction&);
    3738   
    3839    ///
    39     /// @todo doc
     40    /// @todo remove
    4041    ///
    4142    Kernel_SEV(const Kernel_SEV& kernel, const std::vector<size_t>& index);
     
    4445    /// @return element at position (\a row, \a column) in the Kernel
    4546    /// matrix
    46     ///
     47    ///
    4748    inline double operator()(const size_t row,const size_t column) const
    4849    { return kernel_matrix_(row,column); }
    4950
     51    ///
     52    /// Calculates the scalar product using the KernelFunction between
     53    /// data vector @a vec and column \f$i\f$ in data matrix.
    5054    ///
    5155    /// @return kernel element between data @a vec and training sample @a i
     
    5458
    5559    ///
    56     /// @todo doc
     60    /// Using the KernelFunction this function calculates the scalar
     61    /// product between vector @a vec and the column \f$ i\f$ in data
     62    /// matrix. The KernelFunction expects a weight vector for each of
     63    /// the two data vectors and as this Kernel is non-weighted each
     64    /// value in the data matrix is associated to a unity weight.
     65    ///
     66    /// @return weighted kernel element between data @a vec and
     67    /// training sample @a i
    5768    ///
    5869    double element(const DataLookup1D& vec, const DataLookup1D& w,
     
    6071
    6172    ///
    62     /// @todo doc
     73    /// @todo remove this function
    6374    ///
    6475    const Kernel* selected(const std::vector<size_t>& index) const;
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