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);
}