extl/intelligence/ann/kfold_cross_validator.h

   1 /* ///////////////////////////////////////////////////////////////////////
   2  * File:                kfold_cross_validator.h
   3  *
   4  * Created:             09.04.05
   5  * Updated:             09.04.05
   6  *
   7  * Brief:               The kfold_cross_validator class
   8  *
   9  * [<Home>]
  10  * Copyright (c) 2008-2020, Waruqi All rights reserved.
  11  * //////////////////////////////////////////////////////////////////// */
  12
  13 #ifndef EXTL_INTELLIGENCE_ANN_KFOLD_CROSS_VALIDATOR_H
  14 #define EXTL_INTELLIGENCE_ANN_KFOLD_CROSS_VALIDATOR_H
  15
  16 /*!\file kfold_cross_validator.h
  17  * \brief kfold_cross_validator class
  18  */
  19
  20 /* ///////////////////////////////////////////////////////////////////////
  21  * Compatibility
  22  */
  23 #if !defined(EXTL_INTELLIGENCE_ANN_NETWORK_SUPPORT)
  24 #       error kfold_cross_validator.h is not supported by the current compiler.
  25 #endif
  26
  27 /* ///////////////////////////////////////////////////////////////////////
  28  * Includes
  29  */
  30 #include "prefix.h"
  31
  32 /* ///////////////////////////////////////////////////////////////////////
  33  * ::extl::intelligence namespace
  34  */
  35 EXTL_INTELLIGENCE_BEGIN_WHOLE_NAMESPACE
  36
  37
  38 /*!brief kfold_cross_validator
  39  *
  40  * \param NetWork the networks type
  41  * \param NetVdtr the network validator type
  42  * \param K k-fold validation
  43  *
  44  * \ingroup extl_group_intelligence
  45  */
  46 template<       typename_param_k NetWork
  47                 ,       typename_param_k NetVdtr
  48                 ,       e_size_t K = 10
  49                 >
  50 class kfold_cross_validator
  51 {
  52         /// \name Types
  53         /// @{
  54         public:
  55                 typedef kfold_cross_validator                                                                                           class_type;
  56                 typedef NetWork                                                                                                                         network_type;
  57                 typedef typename_type_k network_type::size_type                                                         size_type;
  58                 typedef typename_type_k network_type::bool_type                                                         bool_type;
  59                 typedef typename_type_k network_type::index_type                                                        index_type;
  60                 typedef typename_type_k network_type::float_type                                                        float_type;
  61                 typedef typename_type_k network_type::sample_type                                                       sample_type;
  62                 typedef typename_type_k network_type::samples_type                                                      samples_type;
  63                 typedef NetVdtr                                                                                                                         validator_type;
  64         /// @}
  65
  66         /// \name Members
  67         /// @{
  68         private:
  69                 /// the mean square error, range: [0, 1]
  70                 float_type                                                                                                                                      m_mse;
  71                 /// the error rate, range: [0, 1]
  72                 float_type                                                                                                                                      m_erate;
  73                 /// network validator
  74                 validator_type                                                                                                                          m_validator;
  75         /// @}
  76
  77         /// \name Constants
  78         /// @{
  79         public:
  80                 enum { en_kfold = K     };
  81         /// @}
  82
  83         /// \name Constructors
  84         /// @{
  85         public:
  86                 kfold_cross_validator()
  87                         : m_mse(0)
  88                         , m_erate(0)
  89                 {
  90                 }
  91         /// @}
  92
  93         /// \name Attributes
  94         /// @{
  95         public:
  96                 /// returns the mean square error, range: [0, 1]
  97                 float_type                                      mse() const                                             { return m_mse;                         }
  98
  99                 /// returns the error rate, range: [0, 1]
 100                 float_type                                      erate() const                                   { return m_erate;                       }
 101         /// @}
 102
 103         /// \name Methods
 104         /// @{
 105         public:
 106                 /// \note sps must have real outputs
 107                 void    validate(network_type const& network, samples_type& sps, size_type train_n = 100)
 108                 {
 109                         // initialize mse & error rate
 110                         m_mse = 0;
 111                         m_erate = 0;
 112
 113                         size_type sps_n = sps.size();
 114                         EXTL_ASSERT(size_type(en_kfold) <= sps_n);
 115
 116                         // validate samples
 117                         size_type part_n = sps_n / en_kfold;
 118                         for (index_type k = 0; k < en_kfold; ++k)
 119                         {
 120                                 // calculates validated range
 121                                 index_type b = part_n * k;
 122                                 index_type e = part_n * (k + 1);
 123                                 if (k == en_kfold - 1) e = sps_n;
 124
 125                                 samples_type vsps;      // validated samples
 126                                 samples_type tsps;      // trained samples
 127                                 for (index_type i = 0; i < sps_n; ++i)
 128                                 {
 129                                         // split samples
 130                                         if (i >= b && i < e) vsps.push_back(sps[i]);
 131                                         else tsps.push_back(sps[i]);
 132                                 }
 133
 134                                 // train network
 135                                 network_type net(network);
 136                                 net.init();
 137                                 net.train(tsps, train_n);
 138                                 m_validator.validate(net, vsps);
 139
 140                                 // validate network
 141                                 m_mse += m_validator.mse();
 142                                 m_erate += m_validator.erate();
 143                         }
 144
 145                         m_mse /= en_kfold;
 146                         m_erate /= en_kfold;
 147                 }
 148         /// @}
 149 };
 150
 151
 152 /* ///////////////////////////////////////////////////////////////////////
 153  * ::extl::intelligence namespace
 154  */
 155 EXTL_INTELLIGENCE_END_WHOLE_NAMESPACE
 156
 157 /* //////////////////////////////////////////////////////////////////// */
 158 #endif  /* EXTL_INTELLIGENCE_ANN_KFOLD_CROSS_VALIDATOR_H */
 159 /* //////////////////////////////////////////////////////////////////// */