ENH: Method run_k_fold_test overloaded, so that it can output not only to...

ENH: Method run_k_fold_test overloaded, so that it can output not only to STDOUT, but also to the file, either according to its name or to the open handler.

src/CrossValidator/CrossValidator.cpp

@@ -3,7 +3,7 @@
 //
 
 #include "CrossValidator.h"
-#include "../message.h"
+#include "message.h"
 
 namespace lib4neuro {
     LIB4NEURO_API CrossValidator::CrossValidator(ILearningMethods* optimizer, ErrorFunction* ef) {
@@ -11,19 +11,63 @@ namespace lib4neuro {
         this->ef = ef;
     }
 
-    LIB4NEURO_API void CrossValidator::run_k_fold_test(unsigned int k, unsigned int tests_number) {
+    LIB4NEURO_API void CrossValidator::run_k_fold_test(unsigned int k, unsigned int tests_number, std::ofstream* results_file_path) {
+        //TODO do not duplicate code - write in a more elegant way
         NeuralNetwork *net = this->ef->get_network_instance();
 
+        double cv_err_sum = 0;
+
+        for(unsigned int i = 0; i < tests_number; i++) {
+            COUT_INFO("Cross-validation run " << i+1 << std::endl);
+            *results_file_path << "Cross-validation run " << i+1 << std::endl;
+
+            this->ef->divide_data_train_test(1.0/k);
+            *results_file_path << "Number of train data points: " << this->ef->get_dataset()->get_n_elements() << std::endl;
+            *results_file_path << "Number of test data points: " << this->ef->get_test_dataset()->get_n_elements() << std::endl;
+            net->randomize_parameters();
+            net->scale_parameters( 1.0 / (net->get_n_weights() + net->get_n_biases()));
+            this->optimizer->optimize(*this->ef);
+
+            /* Error evaluation and writing */
+            double err = this->ef->eval_on_test_data(results_file_path);
+            cv_err_sum += err;
+            COUT_INFO("CV error (run " << i+1 << "): " << err << std::endl << std::endl);
+
+            this->ef->return_full_data_set_for_training();
+        }
+
+        COUT_INFO("CV error mean: " << cv_err_sum/tests_number << std::endl);
+        *results_file_path << "CV error mean: " << cv_err_sum/tests_number << std::endl;
+    }
+
+    LIB4NEURO_API void CrossValidator::run_k_fold_test(unsigned int k, unsigned int tests_number, std::string results_file_path) {
+        NeuralNetwork *net = this->ef->get_network_instance();
+
+        double cv_err_sum = 0;
+
         for(unsigned int i = 0; i < tests_number; i++) {
-            COUT_DEBUG(<< "Cross-validation run " << i+1 << std::endl);
+            COUT_INFO("Cross-validation run " << i+1 << std::endl);
 
             this->ef->divide_data_train_test(1.0/k);
-            COUT_DEBUG(<< "number of train data points: " << this->ef->get_dataset()->get_n_elements() << std::endl);
+            COUT_DEBUG("Number of train data points: " << this->ef->get_dataset()->get_n_elements() << std::endl);
+            COUT_DEBUG("Number of test data points: " << this->ef->get_test_dataset()->get_n_elements() << std::endl);
             net->randomize_parameters();
             net->scale_parameters( 1.0 / (net->get_n_weights() + net->get_n_biases()));
-            net->print_weights();
             this->optimizer->optimize(*this->ef);
+
+            /* Error evaluation and writing */
+            double err;
+            if(results_file_path == "") {
+                err = this->ef->eval_on_test_data();
+            } else {
+                err = this->ef->eval_on_test_data(results_file_path + "_cv" + std::to_string(i) + ".dat");
+            }
+            cv_err_sum += err;
+            COUT_INFO("CV error (run " << i+1 << "): " << err << std::endl << std::endl);
+
             this->ef->return_full_data_set_for_training();
         }
+
+        COUT_INFO("CV error mean: " << cv_err_sum/tests_number << std::endl);
     }
 }

src/CrossValidator/CrossValidator.h

@@ -36,12 +36,22 @@ namespace lib4neuro {
          */
         LIB4NEURO_API CrossValidator(ILearningMethods* optimizer, ErrorFunction* ef);
 
+        /**
+         *
+         * @param k
+         * @param test_number
+         * @param results_file_path
+         */
+        LIB4NEURO_API void
+        run_k_fold_test(unsigned int k, unsigned int test_number, std::string results_file_path = "");
+
         /**
          *
          * @param k
          * @param tests_number
+         * @param results_file_path
          */
-        LIB4NEURO_API void run_k_fold_test(unsigned int k, unsigned int test_number);
+        LIB4NEURO_API void run_k_fold_test(unsigned int k, unsigned int tests_number, std::ofstream* results_file_path);
     };
 }