From 44ee25894419475c3017af840c820e6c3a26a971 Mon Sep 17 00:00:00 2001
From: Martin Beseda <martin.beseda@vsb.cz>
Date: Sun, 6 Jan 2019 09:33:48 +0100
Subject: [PATCH] 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 | 54 ++++++++++++++++++++++++---
src/CrossValidator/CrossValidator.h | 12 +++++-
2 files changed, 60 insertions(+), 6 deletions(-)
diff --git a/src/CrossValidator/CrossValidator.cpp b/src/CrossValidator/CrossValidator.cpp
index 970c7fbf..35449264 100644
--- a/src/CrossValidator/CrossValidator.cpp
+++ b/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);
}
}
diff --git a/src/CrossValidator/CrossValidator.h b/src/CrossValidator/CrossValidator.h
index a6db416d..8ee16286 100644
--- a/src/CrossValidator/CrossValidator.h
+++ b/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);
};
}
--
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