SolutionsError::SolutionsError(const tinyxml2::XMLDocument& solutions_error_document) : PerformanceTerm(solutions_error_document) { set_default(); from_XML(solutions_error_document); }
NeuralParametersNorm::NeuralParametersNorm(const tinyxml2::XMLDocument& neural_parameters_norm_document) : PerformanceTerm() { set_default(); from_XML(neural_parameters_norm_document); }
OutputsIntegrals::OutputsIntegrals(const tinyxml2::XMLDocument& outputs_integrals_document) : PerformanceTerm(outputs_integrals_document) { set_default(); from_XML(outputs_integrals_document); }
NeuralParametersNorm::NeuralParametersNorm(TiXmlElement* neural_parameters_norm_element) : PerformanceTerm() { set_default(); from_XML(neural_parameters_norm_element); }
void MathematicalModel::load(const std::string& filename) { std::ostringstream buffer; TiXmlDocument document(filename.c_str()); if(!document.LoadFile()) { buffer << "OpenNN Exception: MathematicalModel class.\n" << "void load(const std::string&) method.\n" << "Cannot load XML file " << filename << ".\n"; throw std::logic_error(buffer.str()); } // Mathematical model element TiXmlElement* mathematical_model_element = document.FirstChildElement(); if(!mathematical_model_element) { buffer << "OpenNN Exception: MathematicalModel class.\n" << "void load(const std::string&) method.\n" << "File " << filename << " is not a valid mathematical model file.\n"; throw std::logic_error(buffer.str()); } from_XML(mathematical_model_element); }
OutputsIntegrals::OutputsIntegrals(TiXmlElement* outputs_integrals_element) : PerformanceTerm(outputs_integrals_element) { set_default(); from_XML(outputs_integrals_element); }
MinkowskiError::MinkowskiError(const tinyxml2::XMLDocument& mean_squared_error_document) : ErrorTerm(mean_squared_error_document) { set_default(); from_XML(mean_squared_error_document); }
NeuralParametersNorm::NeuralParametersNorm(const tinyxml2::XMLDocument& neural_parameters_norm_document) : RegularizationTerm() { set_default(); from_XML(neural_parameters_norm_document); }
MinkowskiError::MinkowskiError(TiXmlElement* mean_squared_error_element) : PerformanceTerm(mean_squared_error_element) { set_default(); from_XML(mean_squared_error_element); }
TimeSeriesPredictionTesting::TimeSeriesPredictionTesting(TiXmlElement* time_series_prediction_testing_element) : neural_network_pointer(NULL), data_set_pointer(NULL) { set_default(); from_XML(time_series_prediction_testing_element); }
RegularizationTerm::RegularizationTerm(const tinyxml2::XMLDocument& performance_term_document) : neural_network_pointer(NULL), numerical_differentiation_pointer(NULL) { set_default(); from_XML(performance_term_document); }
TestingAnalysis::TestingAnalysis(const tinyxml2::XMLDocument& testing_analysis_document) : neural_network_pointer(NULL), data_set_pointer(NULL), mathematical_model_pointer(NULL) { set_default(); from_XML(testing_analysis_document); }
InverseProblemTesting::InverseProblemTesting(TiXmlElement* inverse_problem_testing_element) : neural_network_pointer(NULL), data_set_pointer(NULL), mathematical_model_pointer(NULL) { set_default(); from_XML(inverse_problem_testing_element); }
TestingAnalysis::TestingAnalysis(TiXmlElement* testing_analysis_element) : neural_network_pointer(NULL), data_set_pointer(NULL), mathematical_model_pointer(NULL), function_regression_testing_pointer(NULL), pattern_recognition_testing_pointer(NULL), time_series_prediction_testing_pointer(NULL), inverse_problem_testing_pointer(NULL) { set_default(); from_XML(testing_analysis_element); }
void KappaCoefficientOptimizationThreshold::load(const std::string& file_name) { set_default(); tinyxml2::XMLDocument document; if(document.LoadFile(file_name.c_str())) { std::ostringstream buffer; buffer << "OpenNN Exception: KappaCoefficientOptimizationThreshold class.\n" << "void load(const std::string&) method.\n" << "Cannot load XML file " << file_name << ".\n"; throw std::logic_error(buffer.str()); } from_XML(document); }
void SimulatedAnnealingOrder::load(const std::string& file_name) { set_default(); tinyxml2::XMLDocument document; if(document.LoadFile(file_name.c_str())) { std::ostringstream buffer; buffer << "OpenNN Exception: SimulatedAnnealingOrder class.\n" << "void load(const std::string&) method.\n" << "Cannot load XML file " << file_name << ".\n"; throw std::logic_error(buffer.str()); } from_XML(document); }
void InstancesInformation::set(TiXmlElement* instances_information_element) { set(); from_XML(instances_information_element); }
KappaCoefficientOptimizationThreshold::KappaCoefficientOptimizationThreshold(const tinyxml2::XMLDocument& kappa_coefficient_optimization_document) : ThresholdSelectionAlgorithm(kappa_coefficient_optimization_document) { from_XML(kappa_coefficient_optimization_document); }
TrainingAlgorithm::TrainingAlgorithm(const tinyxml2::XMLDocument& document) : performance_functional_pointer(NULL) { from_XML(document); }
TrainingAlgorithm::TrainingAlgorithm(const tinyxml2::XMLDocument& document) : loss_index_pointer(NULL) { from_XML(document); }
void BoundingLayer::set(const tinyxml2::XMLDocument& bounding_layer_document) { set_default(); from_XML(bounding_layer_document); }
MathematicalModel::MathematicalModel(TiXmlElement* mathematical_model_element) { set_default(); from_XML(mathematical_model_element); }
void BoundingLayer::set(TiXmlElement* bounding_layer_element) { from_XML(bounding_layer_element); }
IncrementalOrder::IncrementalOrder(const tinyxml2::XMLDocument& incremental_order_document) : OrderSelectionAlgorithm(incremental_order_document) { from_XML(incremental_order_document); }
Outputs::Outputs(const tinyxml2::XMLDocument& outputs_document) { from_XML(outputs_document); }
void MissingValues::set(const tinyxml2::XMLDocument& document) { set(); from_XML(document); }
GrowingInputs::GrowingInputs(const tinyxml2::XMLDocument& genetic_algorithm_document) : InputsSelectionAlgorithm(genetic_algorithm_document) { from_XML(genetic_algorithm_document); }
void ScalingLayer::set(const tinyxml2::XMLDocument& new_scaling_layer_document) { set_default(); from_XML(new_scaling_layer_document); }
SimulatedAnnealingOrder::SimulatedAnnealingOrder(const tinyxml2::XMLDocument& simulated_annealing_order_document) : OrderSelectionAlgorithm(simulated_annealing_order_document) { from_XML(simulated_annealing_order_document); }
GoldenSectionOrder::GoldenSectionOrder(const tinyxml2::XMLDocument& golden_section_order_document) : OrderSelectionAlgorithm(golden_section_order_document) { from_XML(golden_section_order_document); }