1 | #ifndef _theplu_yat_classifier_kernel_lookup_ |
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2 | #define _theplu_yat_classifier_kernel_lookup_ |
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3 | |
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4 | // $Id$ |
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5 | |
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6 | /* |
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7 | Copyright (C) The authors contributing to this file. |
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8 | |
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9 | This file is part of the yat library, http://lev.thep.lu.se/trac/yat |
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10 | |
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11 | The yat library is free software; you can redistribute it and/or |
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12 | modify it under the terms of the GNU General Public License as |
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13 | published by the Free Software Foundation; either version 2 of the |
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14 | License, or (at your option) any later version. |
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15 | |
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16 | The yat library is distributed in the hope that it will be useful, |
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17 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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18 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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19 | General Public License for more details. |
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20 | |
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21 | You should have received a copy of the GNU General Public License |
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22 | along with this program; if not, write to the Free Software |
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23 | Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA |
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24 | 02111-1307, USA. |
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25 | */ |
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26 | |
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27 | #include "Kernel.h" |
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28 | #include "DataLookup2D.h" |
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29 | #include "MatrixLookup.h" |
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30 | |
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31 | #include <vector> |
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32 | |
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33 | namespace theplu { |
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34 | namespace yat { |
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35 | namespace classifier { |
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36 | |
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37 | class KernelFunction; |
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38 | |
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39 | /// |
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40 | /// @brief Lookup into Kernel |
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41 | /// |
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42 | /// This is the KernelLookup class to be used together with kernel |
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43 | /// methods such as Support Vector Machines (SVM). The class does |
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44 | /// not contain any data or values, but rather is a lookup into a |
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45 | /// Kernel object. Each row and each column corresponds to a row and |
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46 | /// a column in the Kernel, respectively. This design allow for fast |
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47 | /// creation of sub-kernels, which is a common operation in most |
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48 | /// traning/validation procedures. |
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49 | /// |
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50 | /// A KernelLookup can be created directly from a Kernel or from an |
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51 | /// other KernelLookup. In the latter case, the resulting |
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52 | /// KernelLookup is looking directly into the underlying Kernel to |
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53 | /// avoid multiple lookups. |
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54 | /// |
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55 | /// There is a possibility to set the KernelLookup as owner of the |
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56 | /// underlying Kernel. In that case the underlying Kernel will be |
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57 | /// destroyed in the destructor. Consequently, the underlying Kernel |
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58 | /// must have been dynamically allocated and no other KernelLookup |
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59 | /// can own the Kernel. |
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60 | /// |
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61 | class KernelLookup : public DataLookup2D |
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62 | { |
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63 | |
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64 | public: |
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65 | |
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66 | /// |
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67 | /// @brief Constructor a Lookup into a Kernel |
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68 | /// |
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69 | /// Constructs a KernelLookup corresponding to the Kernel @a |
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70 | /// kernel. By default @a owner is set to false, which means |
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71 | /// KernelLookup does not own the underlying Kernel. If |
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72 | /// KernelLookup owns the Kernel the Kernel will be deleted |
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73 | /// in the destructor. |
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74 | /// |
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75 | /// @note If underlying Kernel goes out of scope or is deleted, the |
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76 | /// KernelLookup becomes invalid and the result of further use is |
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77 | /// undefined. |
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78 | /// |
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79 | /// @note Do not construct two KernelLookups from the same @a |
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80 | /// kernel with @a owner set to true because that will cause |
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81 | /// multiple deletion of @a kernel. |
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82 | /// |
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83 | KernelLookup(const Kernel& kernel, const bool owner=false); |
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84 | |
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85 | /// |
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86 | /// @brief Constructing a Lookup into a subKernel |
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87 | /// |
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88 | /// Creating a Lookup into parts of the Kernel. In the created |
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89 | /// Lookup the element in the \f$ i \f$ th row in the \f$ j \f$ th |
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90 | /// column is identical to the element in row row[i] and columns |
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91 | /// column[j] in the underlying @a kernel. If @a owner is set to |
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92 | /// true yhe underlying @a kernel is destroyed in the destructor. |
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93 | /// |
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94 | /// @note If @a kernel goes out of scope or is deleted, the |
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95 | /// returned pointer becomes invalid and the result of further use is |
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96 | /// undefined. |
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97 | /// |
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98 | /// @note For training usage row index shall always be equal to |
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99 | /// column index. |
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100 | /// |
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101 | KernelLookup(const Kernel& kernel, const std::vector<size_t>& row, |
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102 | const std::vector<size_t>& column, const bool owner=false); |
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103 | |
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104 | /// |
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105 | /// @brief Copy constructor. |
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106 | /// |
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107 | /// A Lookup is created looking into the |
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108 | /// same underlying Kernel as @a kl is looking into. The newly |
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109 | /// created KernelLookup does not own the underlying Kernel. |
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110 | /// |
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111 | KernelLookup(const KernelLookup& kl); |
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112 | |
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113 | |
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114 | /// |
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115 | /// @brief Contructing a sub-KernelLookup. |
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116 | /// |
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117 | /// Contructor building a sub-KernelLookup from a KernelLookup |
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118 | /// defined by row index vector and column index vector. In the |
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119 | /// created Lookup the element in the \f$ i \f$ th row in the |
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120 | /// \f$ j \f$ th column is identical to the element in row row[i] and |
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121 | /// columns column[j] in the copied @a kl. The resulting |
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122 | /// KernelLookup is independent of the old KernelLookup, but is |
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123 | /// undefined in case underlying Kernel is destroyed. |
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124 | /// |
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125 | /// @note For training usage row index shall always be equal to |
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126 | /// column index. |
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127 | /// |
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128 | KernelLookup(const KernelLookup& kl, const std::vector<size_t>& row, |
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129 | const std::vector<size_t>& column); |
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130 | |
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131 | /// |
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132 | /// Constructor taking the column (default) or row index vector as |
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133 | /// input. If @a row is false the created KernelLookup will have |
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134 | /// equally many rows as @a kernel. |
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135 | /// |
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136 | /// @note If underlying kernel goes out of scope or is deleted, the |
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137 | /// KernelLookup becomes invalid and the result of further use is |
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138 | /// undefined. |
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139 | /// |
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140 | KernelLookup(const KernelLookup& kernel, const std::vector<size_t>&, |
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141 | const bool row=false); |
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142 | |
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143 | /// |
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144 | /// @brief Destructor |
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145 | /// |
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146 | /// Deletes underlying Kernel if KernelLookup owns it. |
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147 | /// |
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148 | virtual ~KernelLookup(void); |
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149 | |
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150 | |
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151 | /// |
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152 | /// Creates a sub-Kernel identical to the one created using |
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153 | /// KernelLookup(*this, train, train). |
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154 | /// |
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155 | /// @return pointer to dynamically allocated sub-Lookup of the KernelLookup |
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156 | /// |
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157 | /// @Note Returns a dynamically allocated DataLookup2D, which has |
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158 | /// to be deleted by the caller to avoid memory leaks. |
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159 | /// |
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160 | const KernelLookup* training_data(const std::vector<size_t>& train) const; |
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161 | |
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162 | |
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163 | /// |
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164 | /// In returned kernel each row corresponds to a training sample |
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165 | /// and each column corresponds to a validation sample. The |
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166 | /// created sub-KernelLookup is equivalent to using |
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167 | /// KernelLooup(*this, train, validation). |
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168 | /// |
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169 | /// @return sub-Lookup of the DataLookup2D |
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170 | /// |
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171 | /// @Note Returns a dynamically allocated DataLookup2D, which has |
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172 | /// to be deleted by the caller to avoid memory leaks. |
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173 | /// |
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174 | const KernelLookup* |
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175 | validation_data(const std::vector<size_t>& train, |
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176 | const std::vector<size_t>& validation) const; |
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177 | |
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178 | |
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179 | /** |
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180 | This function is useful when predicting on a independent data |
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181 | set using a kernel-based classifier. In returned KernelLookup |
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182 | column \f$ i \f$ corresponds to column \f$ i \f$ in @a |
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183 | data. Row \f$ i \f$ in returned KernelLookup corresponds to |
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184 | same sample as row \f$ i \f$ in @a this. In other words, this |
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185 | function returns a KernelLookup containing the kernel elements |
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186 | between the passed @a data and the internal underlying data @a |
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187 | this was built from. |
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188 | |
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189 | @Note Returns a dynamically allocated DataLookup2D, which has |
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190 | to be deleted by the caller to avoid memory leaks. |
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191 | */ |
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192 | const KernelLookup* test_kernel(const MatrixLookup& data) const; |
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193 | |
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194 | |
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195 | /** |
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196 | This function is useful when predicting on a independent data |
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197 | set using a kernel-based classifier. In returned KernelLookup |
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198 | column \f$ i \f$ corresponds to column \f$ i \f$ in @a |
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199 | data. Row \f$ i \f$ in returned KernelLookup corresponds to |
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200 | same sample as row \f$ i \f$ in @a this. In other words, this |
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201 | function returns a KernelLookup containing the kernel elements |
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202 | between the passed @a data and the internal underlying data @a |
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203 | this was built from. |
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204 | |
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205 | @Note Returns a dynamically allocated DataLookup2D, which has |
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206 | to be deleted by the caller to avoid memory leaks. |
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207 | */ |
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208 | const KernelLookup* test_kernel(const MatrixLookupWeighted& data) const; |
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209 | |
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210 | |
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211 | /// |
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212 | /// @return element at position (\a row, \a column) in the Kernel |
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213 | /// matrix |
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214 | /// |
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215 | inline double operator()(const size_t row,const size_t column) const |
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216 | { return (*kernel_)(row_index_[row],column_index_[column]); } |
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217 | |
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218 | /// |
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219 | /// Each column in returned MatrixLookup corresponds to the column |
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220 | /// in KernelLookup. |
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221 | /// |
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222 | /// @Note Returns a dynamically allocated MatrixLookup, which has |
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223 | /// to be deleted by the caller to avoid memory leaks. |
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224 | /// |
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225 | inline const DataLookup2D* data(void) const |
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226 | { return kernel_->data().training_data(column_index_); } |
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227 | |
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228 | |
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229 | /// |
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230 | /// Function to calculate a new Kernel element using the |
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231 | /// underlying KernelFunction. The value is calulated between @a |
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232 | /// vec and the data vector of the \f$ i \f$ th sample, in other |
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233 | /// words, the sample corresponding to the \f$ i \f$ th row or |
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234 | /// \f$ i \f$ th column. In case KernelLookup is a sub-Kernel and not |
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235 | /// symmetric, the kernel value is calculated between @a vec and |
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236 | /// the data vector corresponding to \f$ i \f$ th row. |
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237 | /// |
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238 | inline double element(const DataLookup1D& vec, const size_t i) const |
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239 | { return kernel_->element(vec, row_index_[i]); } |
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240 | |
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241 | /// |
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242 | /// Function to calculate a new Kernel element using the |
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243 | /// underlying KernelFunction. The value is calulated between @a |
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244 | /// vec and the data vector of the \f$ i \f$ th sample, in other |
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245 | /// words, the sample corresponding to the \f$ i \f$ th row or |
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246 | /// \f$ i \f$ th column. In case KernelLookup is a sub-Kernel and not |
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247 | /// symmetric, the kernel value is calculated between @a vec and |
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248 | /// the data vector corresponding to \f$ i \f$ th row. |
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249 | /// |
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250 | inline double element(const DataLookupWeighted1D& vec, const size_t i) const |
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251 | { return kernel_->element(vec, row_index_[i]); } |
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252 | |
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253 | /// |
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254 | /// Each element in returned KernelLookup is calculated using only |
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255 | /// selected features (defined by @a index). Each element |
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256 | /// corresponds to the same pair of samples as in the original |
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257 | /// KernelLookup. |
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258 | /// |
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259 | /// @Note Returns a dynamically allocated KernelLookup, which has |
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260 | /// to be deleted by the caller to avoid memory leaks. |
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261 | /// |
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262 | const KernelLookup* selected(const std::vector<size_t>& index) const; |
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263 | |
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264 | /// |
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265 | /// @return true if underlying Kernel is weighted |
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266 | /// |
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267 | inline bool weighted(void) const { return kernel_->weighted(); } |
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268 | |
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269 | inline const Kernel* kernel(void) const { return kernel_; } |
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270 | |
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271 | private: |
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272 | const KernelLookup& operator=(const KernelLookup&); |
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273 | |
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274 | const Kernel* kernel_; |
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275 | |
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276 | }; // class KernelLookup |
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277 | |
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278 | }}} // of namespace classifier, yat, and theplu |
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279 | |
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280 | #endif |
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