PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // NeighborhoodConditionalMean.h 00004 // 00005 // Copyright (C) 2006 Dan Popovici 00006 // 00007 // Redistribution and use in source and binary forms, with or without 00008 // modification, are permitted provided that the following conditions are met: 00009 // 00010 // 1. Redistributions of source code must retain the above copyright 00011 // notice, this list of conditions and the following disclaimer. 00012 // 00013 // 2. Redistributions in binary form must reproduce the above copyright 00014 // notice, this list of conditions and the following disclaimer in the 00015 // documentation and/or other materials provided with the distribution. 00016 // 00017 // 3. The name of the authors may not be used to endorse or promote 00018 // products derived from this software without specific prior written 00019 // permission. 00020 // 00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR 00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN 00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED 00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00031 // 00032 // This file is part of the PLearn library. For more information on the PLearn 00033 // library, go to the PLearn Web site at www.plearn.org 00034 00035 // Authors: Dan Popovici 00036 00040 #ifndef NeighborhoodConditionalMean_INC 00041 #define NeighborhoodConditionalMean_INC 00042 00043 #include <plearn_learners/generic/PLearner.h> 00044 #include <plearn_learners/testers/PTester.h> 00045 #include <plearn/vmat/FileVMatrix.h> 00046 #include <plearn/vmat/MemoryVMatrix.h> 00047 #include <plearn/io/load_and_save.h> 00048 #include <plearn/io/fileutils.h> 00049 #include <plearn/math/random.h> 00050 #include <plearn/vmat/ExplicitSplitter.h> 00051 #include <plearn_learners/nearest_neighbors/BallTreeNearestNeighbors.h> 00052 #include <plearn_learners/second_iteration/CovariancePreservationImputationVMatrix.h> 00053 #include <plearn_learners/second_iteration/NeighborhoodImputationVMatrix.h> 00054 #include <plearn_learners/second_iteration/Experimentation.h> 00055 00056 namespace PLearn { 00057 00062 class NeighborhoodConditionalMean : public PLearner 00063 { 00064 typedef PLearner inherited; 00065 00066 public: 00067 00068 //##### Public Build Options ############################################ 00069 00072 00074 VMat test_train_input_set; 00076 VMat test_train_target_set; 00078 int number_of_test_samples; 00080 int number_of_train_samples; 00082 TVec<string> target_field_names; 00083 PPath train_covariance_file_name; 00084 PPath test_train_covariance_file_name; 00086 TVec<int> various_ks; 00088 Vec deletion_thresholds; 00090 string experiment_name; 00092 TVec< string > missing_indicator_field_names; 00094 PP< PTester > experiment_template; 00095 00096 public: 00097 //##### Public Member Functions ######################################### 00098 00100 // ### Make sure the implementation in the .cc 00101 // ### initializes all fields to reasonable default values. 00102 NeighborhoodConditionalMean(); 00103 int outputsize() const; 00104 void train(); 00105 void computeOutput(const Vec&, Vec&) const; 00106 void computeCostsFromOutputs(const Vec&, const Vec&, const Vec&, Vec&) const; 00107 TVec<string> getTestCostNames() const; 00108 TVec<string> getTrainCostNames() const; 00109 00110 00111 //##### PLearn::Object Protocol ######################################### 00112 00113 // Declares other standard object methods. 00114 // ### If your class is not instantiatable (it has pure virtual methods) 00115 // ### you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT_METHODS 00116 PLEARN_DECLARE_OBJECT(NeighborhoodConditionalMean); 00117 00118 // Simply calls inherited::build() then build_() 00119 virtual void build(); 00120 00122 // (PLEASE IMPLEMENT IN .cc) 00123 virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies); 00124 00125 protected: 00126 //##### Protected Member Functions ###################################### 00127 00129 static void declareOptions(OptionList& ol); 00130 00131 private: 00132 //##### Private Member Functions ######################################## 00133 00135 void build_(); 00136 void computeNeighborhood(); 00137 void experimentWithVariousKs(); 00138 void createMasterHeaderFile(); 00139 void getMasterHeaderRecords(); 00140 void updateMasterHeaderRecords(int row, int col); 00141 00142 private: 00143 //##### Private Data Members ############################################ 00144 00145 // The rest of the private stuff goes here 00146 ProgressBar* pb; 00147 VMat train_covariance_file; 00148 CovariancePreservationImputationVMatrix* train_covariance_vmatrix; 00149 VMat train_covariance_vmat; 00150 Vec train_covariance_vector; 00151 VMat test_train_covariance_file; 00152 CovariancePreservationImputationVMatrix* test_train_covariance_vmatrix; 00153 VMat test_train_covariance_vmat; 00154 Vec test_train_covariance_vector; 00155 PPath test_train_neighborhood_file_name; 00156 BallTreeNearestNeighbors* test_train_neighborhood_learner; 00157 VMat test_train_neighborhood_file; 00158 Vec test_train_neighborhood_vector; 00159 PPath master_header_file_name; 00160 VMat master_header_file; 00161 int master_header_length; 00162 int master_header_width; 00163 int master_header_row; 00164 int master_header_col; 00165 TVec<string> master_header_names; 00166 Mat master_header_records; 00167 int to_deal_with_k; 00168 string to_deal_with_target; 00169 int to_deal_with_ind; 00170 NeighborhoodImputationVMatrix* test_train_neighbor_imputation_vmatrix; 00171 VMat test_train_neighbor_imputation_vmat; 00172 VMat test_train_neighbor_imputation_file; 00173 Vec test_train_neighbor_imputation_vector; 00174 Experimentation* experimentation_learner; 00175 00176 /* 00177 int main_row; 00178 int main_col; 00179 int main_length; 00180 int main_width; 00181 Vec main_input; 00182 TVec<string> main_names; 00183 StatsCollector main_stats; 00184 PPath main_metadata; 00185 TVec<int> main_ins; 00186 real main_total; 00187 real main_missing; 00188 real main_present; 00189 int targeted_length; 00190 int targeted_width; 00191 Vec targeted_input; 00192 TVec<string> targeted_names; 00193 StatsCollector targeted_stats; 00194 PPath targeted_metadata; 00195 real targeted_missing; 00196 PPath header_file_name; 00197 VMat header_file; 00198 Vec header_record; 00199 int fields_col; 00200 int fields_width; 00201 TVec<int> fields_selected; 00202 int to_deal_with_total; 00203 int to_deal_with_next; 00204 real to_deal_with_value; 00205 string to_deal_with_name; 00206 int ind_next; 00207 int output_length; 00208 int output_width; 00209 int output_col; 00210 string output_path; 00211 TVec<string> output_names; 00212 Vec output_vec; 00213 TVec<int> output_variable_src; 00214 VMat output_file; 00215 int train_test_length; 00216 string train_test_path; 00217 TVec<int> train_test_variable_src; 00218 VMat train_test_file; 00219 PP<PTester> cond_mean; 00220 PPath results_file_name; 00221 VMat results_file; 00222 int results_length; 00223 real results_nstages; 00224 real results_mse; 00225 real results_std_err; 00226 PPath test_output_file_name; 00227 VMat test_output_file; 00228 int test_output_length; 00229 */ 00230 }; 00231 00232 // Declares a few other classes and functions related to this class 00233 DECLARE_OBJECT_PTR(NeighborhoodConditionalMean); 00234 00235 } // end of namespace PLearn 00236 00237 #endif 00238 00239 00240 /* 00241 Local Variables: 00242 mode:c++ 00243 c-basic-offset:4 00244 c-file-style:"stroustrup" 00245 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00246 indent-tabs-mode:nil 00247 fill-column:79 00248 End: 00249 */ 00250 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :