OpenNN::InverseSumSquaredError Class Reference

#include <inverse_sum_squared_error.h>

Inheritance diagram for OpenNN::InverseSumSquaredError:

OpenNN::PerformanceTerm

List of all members.

Public Types

enum  UnknownsMethod { LookUpTable, IndependentParametersValues }

Public Member Functions

 InverseSumSquaredError (void)
 InverseSumSquaredError (NeuralNetwork *)
 InverseSumSquaredError (NeuralNetwork *, MathematicalModel *, DataSet *)
 InverseSumSquaredError (TiXmlElement *)
virtual ~InverseSumSquaredError (void)
const UnknownsMethodget_unknowns_method (void) const
std::string write_unknowns_method (void) const
void set_unknowns_method (const UnknownsMethod &)
void set_unknowns_method (const std::string &)
void set_default (void)
void check (void) const
double calculate_evaluation (void) const
double calculate_evaluation (const Vector< double > &) const
double calculate_generalization_evaluation (void) const
std::string write_performance_term_type (void) const
TiXmlElement * to_XML (void) const
void from_XML (TiXmlElement *)


Detailed Description

This class represents the concept of sum squared error for inverse problems. It measures the difference between the outputs from a mathematical model and the targets in a data set. This performance term is used in inverse problems.

Definition at line 33 of file inverse_sum_squared_error.h.


Member Enumeration Documentation

Enumeration of the different methods for putting the unknowns into the mathematical model.

Definition at line 62 of file inverse_sum_squared_error.h.


Constructor & Destructor Documentation

OpenNN::InverseSumSquaredError::InverseSumSquaredError ( void   )  [explicit]

Default constructor. It creates an inverse sum squared error performance term not associated to any neural network and not measured on any mathematical model and data set. It also initializes all the rest of class members to their default values.

Definition at line 41 of file inverse_sum_squared_error.cpp.

OpenNN::InverseSumSquaredError::InverseSumSquaredError ( NeuralNetwork new_neural_network_pointer  )  [explicit]

Neural network constructor. It creates an inverse sum squared error associated to a neural network but neither measured on a mathematical model nor on a data set. It also initializes all the rest of class members to their default values.

Parameters:
new_neural_network_pointer Pointer to a neural network object.

Definition at line 55 of file inverse_sum_squared_error.cpp.

OpenNN::InverseSumSquaredError::InverseSumSquaredError ( NeuralNetwork new_neural_network_pointer,
MathematicalModel new_mathematical_model_pointer,
DataSet new_data_set_pointer 
) [explicit]

Neural network, mathematical model and data set constructor. It creates an inverse sum squared error associated to a neural network and measured on a mathematical model and a data set. It also initializes all the rest of class members to their default values.

Parameters:
new_neural_network_pointer Pointer to a neural network object.
new_mathematical_model_pointer Pointer to a mathematical model object.
new_data_set_pointer Pointer to a data set object.

Definition at line 73 of file inverse_sum_squared_error.cpp.

OpenNN::InverseSumSquaredError::InverseSumSquaredError ( TiXmlElement *  inverse_sum_squared_error_element  )  [explicit]

XML constructor. It creates an inverse sum squared error performance term not associated to any neural network and not measured on any mathematical model and data set. It initializes all the member data from a XML element.

Parameters:
inverse_sum_squared_error_element Pointer to a Tiny XML element containing the inverse sum squared error data.

Definition at line 89 of file inverse_sum_squared_error.cpp.

OpenNN::InverseSumSquaredError::~InverseSumSquaredError ( void   )  [virtual]

Destructor. It does not delete any object.

Definition at line 102 of file inverse_sum_squared_error.cpp.


Member Function Documentation

const InverseSumSquaredError::UnknownsMethod & OpenNN::InverseSumSquaredError::get_unknowns_method ( void   )  const

This returns the method for entering the unknown values or functions into the mathematical model.

Definition at line 113 of file inverse_sum_squared_error.cpp.

std::string OpenNN::InverseSumSquaredError::write_unknowns_method ( void   )  const

This returns a string with the name of the method for entering the unknown values or functions into the mathematical model.

Definition at line 123 of file inverse_sum_squared_error.cpp.

void OpenNN::InverseSumSquaredError::set_unknowns_method ( const UnknownsMethod new_unknowns_method  ) 

This sets a new the method for entering the unknown values or functions into the mathematical model.

Parameters:
new_unknowns_method Unknowns method (independent parameters, look-up table, ...).

Definition at line 159 of file inverse_sum_squared_error.cpp.

void OpenNN::InverseSumSquaredError::set_unknowns_method ( const std::string &  new_unknowns_method  ) 

This sets a new the method for entering the unknown values or functions into the mathematical model.

Parameters:
new_unknowns_method String with the name of the unknowns method (independent parameters, look-up table, ...).

Definition at line 170 of file inverse_sum_squared_error.cpp.

void OpenNN::InverseSumSquaredError::set_default ( void   )  [virtual]

This method sets the default values of the inverse sum squared error:

  • Unknowns method: Independent parameters values.
  • Display: true.

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 201 of file inverse_sum_squared_error.cpp.

void OpenNN::InverseSumSquaredError::check ( void   )  const [virtual]

This method checks that there are a neural network, a mathemacial model and a data set associated to the inverse sum squared error. If some of the above conditions is not hold, the method throws an exception.

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 214 of file inverse_sum_squared_error.cpp.

double OpenNN::InverseSumSquaredError::calculate_evaluation ( void   )  const [virtual]

Todo:

Implements OpenNN::PerformanceTerm.

Definition at line 292 of file inverse_sum_squared_error.cpp.

double OpenNN::InverseSumSquaredError::calculate_evaluation ( const Vector< double > &   )  const [virtual]

This method returns the default evaluation of a performance term for a given set of neural network parameters.

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 319 of file inverse_sum_squared_error.cpp.

double OpenNN::InverseSumSquaredError::calculate_generalization_evaluation ( void   )  const [virtual]

Todo:

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 364 of file inverse_sum_squared_error.cpp.

std::string OpenNN::InverseSumSquaredError::write_performance_term_type ( void   )  const [virtual]

This method returns a string with the name of the inverser sum squared error performance type, "INVERSE_SUM_SQUARED_ERROR".

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 416 of file inverse_sum_squared_error.cpp.

TiXmlElement * OpenNN::InverseSumSquaredError::to_XML ( void   )  const [virtual]

This method serializes the inverse sum squared error object into a XML element of the TinyXML library. See the OpenNN manual for more information about the format of this element.

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 427 of file inverse_sum_squared_error.cpp.

void OpenNN::InverseSumSquaredError::from_XML ( TiXmlElement *   )  [virtual]

Todo:

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 475 of file inverse_sum_squared_error.cpp.


The documentation for this class was generated from the following files:

Generated on Sun Aug 26 11:58:19 2012 for OpenNN by  doxygen 1.5.9