OpenNN::PerformanceTerm Class Reference

#include <performance_term.h>

Inheritance diagram for OpenNN::PerformanceTerm:

OpenNN::CrossEntropyError OpenNN::FinalSolutionsError OpenNN::IndependentParametersError OpenNN::InverseSumSquaredError OpenNN::MeanSquaredError OpenNN::MinkowskiError OpenNN::NeuralParametersNorm OpenNN::NormalizedSquaredError OpenNN::OutputsIntegrals OpenNN::RootMeanSquaredError OpenNN::SolutionsError OpenNN::SumSquaredError

List of all members.

Classes

struct  FirstOrderEvaluation
struct  FirstOrderEvaluationTerms
struct  SecondOrderEvaluation
struct  ZeroOrderEvaluation

Public Member Functions

 PerformanceTerm (void)
 PerformanceTerm (NeuralNetwork *)
 PerformanceTerm (DataSet *)
 PerformanceTerm (MathematicalModel *)
 PerformanceTerm (NeuralNetwork *, DataSet *)
 PerformanceTerm (NeuralNetwork *, MathematicalModel *)
 PerformanceTerm (NeuralNetwork *, MathematicalModel *, DataSet *)
 PerformanceTerm (TiXmlElement *)
 PerformanceTerm (const PerformanceTerm &)
virtual ~PerformanceTerm (void)
virtual PerformanceTermoperator= (const PerformanceTerm &)
virtual bool operator== (const PerformanceTerm &) const
NeuralNetworkget_neural_network_pointer (void) const
MathematicalModelget_mathemtaical_model_pointer (void) const
DataSetget_data_set_pointer (void) const
NumericalDifferentiationget_numerical_differentiation_pointer (void) const
const bool & get_display (void) const
virtual void set (void)
virtual void set (NeuralNetwork *)
virtual void set (DataSet *)
virtual void set (MathematicalModel *)
virtual void set (NeuralNetwork *, DataSet *)
virtual void set (NeuralNetwork *, MathematicalModel *)
virtual void set (NeuralNetwork *, MathematicalModel *, DataSet *)
virtual void set (const PerformanceTerm &)
virtual void set_neural_network_pointer (NeuralNetwork *)
virtual void set_mathematical_model_pointer (MathematicalModel *)
virtual void set_data_set_pointer (DataSet *)
void set_numerical_differentiation_pointer (NumericalDifferentiation *)
virtual void set_default (void)
void set_display (const bool &)
void construct_numerical_differentiation (void)
void delete_numerical_differentiation_pointer (void)
virtual void check (void) const
Vector< Vector< double > > calculate_layers_delta (const Vector< Vector< double > > &, const Vector< double > &) const
Vector< Vector< double > > calculate_layers_delta (const Vector< Vector< double > > &, const Vector< double > &, const Vector< double > &) const
Matrix< Matrix< double > > calculate_interlayers_Delta (const Vector< Vector< double > > &, const Vector< Vector< double > > &, const Matrix< Matrix< double > > &, const Vector< double > &, const Matrix< double > &, const Vector< Vector< double > > &) const
Vector< double > calculate_point_gradient (const Vector< double > &, const Vector< Vector< double > > &, const Vector< Vector< double > > &) const
Vector< double > calculate_point_gradient (const Vector< Matrix< double > > &, const Vector< Vector< double > > &) const
Matrix< double > calculate_point_Hessian (const Vector< Vector< double > > &, const Vector< Vector< Vector< double > > > &, const Matrix< Matrix< double > > &, const Vector< Vector< double > > &, const Matrix< Matrix< double > > &) const
virtual double calculate_evaluation (void) const =0
virtual double calculate_evaluation (const Vector< double > &) const
virtual double calculate_generalization_evaluation (void) const
virtual Vector< double > calculate_gradient (void) const
virtual Matrix< double > calculate_Hessian (void) const
virtual Vector< double > calculate_evaluation_terms (void) const
virtual Vector< double > calculate_evaluation_terms (const Vector< double > &) const
virtual Matrix< double > calculate_Jacobian_terms (void) const
virtual
PerformanceTerm::FirstOrderEvaluationTerms 
calculate_first_order_evaluation_terms (void) const
virtual std::string write_performance_term_type (void) const
virtual std::string write_information (void) const
virtual std::string to_string (void) const
virtual TiXmlElement * to_XML (void) const
virtual void from_XML (TiXmlElement *)
unsigned int calculate_Kronecker_delta (const unsigned int &, const unsigned int &) const

Protected Attributes

NeuralNetworkneural_network_pointer
DataSetdata_set_pointer
MathematicalModelmathematical_model_pointer
NumericalDifferentiationnumerical_differentiation_pointer
bool display


Detailed Description

This class represents the concept of performance term. A performance term is a summand in the performance functional expression. Any derived class must implement the calculate_evaluation(void) method.

Definition at line 45 of file performance_term.h.


Constructor & Destructor Documentation

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

Default constructor. It creates a default performance term object, with all pointers initialized to NULL. It also initializes all the rest of class members to their default values.

Definition at line 46 of file performance_term.cpp.

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

Neural network constructor. It creates a performance term object associated to a neural network object. The rest of pointers are initialized to NULL. 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 64 of file performance_term.cpp.

OpenNN::PerformanceTerm::PerformanceTerm ( DataSet new_data_set_pointer  )  [explicit]

Data set constructor. It creates a performance term object associated to a given data set object. The rest of pointers are initialized to NULL. It also initializes all the rest of class members to their default values.

Parameters:
new_data_set_pointer Pointer to a data set object.

Definition at line 82 of file performance_term.cpp.

OpenNN::PerformanceTerm::PerformanceTerm ( MathematicalModel new_mathematical_model_pointer  )  [explicit]

Mathematical model constructor. It creates a performance term object associated to a given mathematical model object. The rest of pointers are initialized to NULL. It also initializes all the rest of class members to their default values.

Parameters:
new_mathematical_model_pointer Pointer to a mathematical model object.

Definition at line 100 of file performance_term.cpp.

OpenNN::PerformanceTerm::PerformanceTerm ( NeuralNetwork new_neural_network_pointer,
DataSet new_data_set_pointer 
) [explicit]

Neural network and data set constructor. It creates a performance term object associated to a neural network and to be measured on a data set. The rest of pointers are initialized to NULL. 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_data_set_pointer Pointer to a data set object.

Definition at line 119 of file performance_term.cpp.

OpenNN::PerformanceTerm::PerformanceTerm ( NeuralNetwork new_neural_network_pointer,
MathematicalModel new_mathematical_model_pointer 
) [explicit]

Neural network and mathematical model constructor. It creates a performance term object associated to a neural network and to be measured on a mathematical model. The rest of pointers are initialized to NULL. 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.

Definition at line 138 of file performance_term.cpp.

OpenNN::PerformanceTerm::PerformanceTerm ( 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 a performance term object associated to a neural network and to be measured on both a mathematical model and a data set. The rest of pointers are initialized to NULL. 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 158 of file performance_term.cpp.

OpenNN::PerformanceTerm::PerformanceTerm ( TiXmlElement *  performance_term_element  )  [explicit]

XML constructor. It creates a default performance term object, with all pointers initialized to NULL. It also loads all the rest of class members from a XML element.

Parameters:
performance_term_element Pointer to a TinyXML element with the object data.

Definition at line 175 of file performance_term.cpp.

OpenNN::PerformanceTerm::PerformanceTerm ( const PerformanceTerm other_performance_term  ) 

Copy constructor. It creates a copy of an existing performance term object.

Parameters:
other_performance_term Performance term object to be copied.

Definition at line 193 of file performance_term.cpp.

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

Destructor. It deletes the numerical differentiation object composing this performance term object.

Definition at line 218 of file performance_term.cpp.


Member Function Documentation

PerformanceTerm & OpenNN::PerformanceTerm::operator= ( const PerformanceTerm other_performance_term  )  [virtual]

Assignment operator. It assigns to this performance term object the members from another performance term object.

Parameters:
other_performance_term Performance term object to be copied.

Definition at line 232 of file performance_term.cpp.

bool OpenNN::PerformanceTerm::operator== ( const PerformanceTerm other_performance_term  )  const [virtual]

Equal to operator. It compares this object to another object. The return is true if both objects have the same member data, and false otherwise.

Definition at line 255 of file performance_term.cpp.

NeuralNetwork* OpenNN::PerformanceTerm::get_neural_network_pointer ( void   )  const [inline]

This method returns a pointer to the neural network object associated to the performance term.

Definition at line 165 of file performance_term.h.

MathematicalModel* OpenNN::PerformanceTerm::get_mathemtaical_model_pointer ( void   )  const [inline]

This method returns a pointer to the mathematical model object associated to the performance term.

Definition at line 173 of file performance_term.h.

DataSet* OpenNN::PerformanceTerm::get_data_set_pointer ( void   )  const [inline]

This method returns a pointer to the data set object associated to the performance term.

Definition at line 181 of file performance_term.h.

NumericalDifferentiation* OpenNN::PerformanceTerm::get_numerical_differentiation_pointer ( void   )  const [inline]

This method returns a pointer to the numerical differentiation object used in this performance term object.

Definition at line 189 of file performance_term.h.

const bool & OpenNN::PerformanceTerm::get_display ( void   )  const

This method returns true if messages from this class can be displayed on the screen, or false if messages from this class can't be displayed on the screen.

Definition at line 279 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set ( void   )  [virtual]

This method sets all the member pointers to NULL (neural network, data set, mathematical model and numerical differentiation). It also initializes all the rest of class members to their default values.

Reimplemented in OpenNN::FinalSolutionsError.

Definition at line 290 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set ( NeuralNetwork new_neural_network_pointer  )  [virtual]

This method sets all the member pointers to NULL, but the neural network, which set to a given pointer. It also initializes all the rest of class members to their default values.

Parameters:
new_neural_network_pointer Pointer to a neural network object.

Reimplemented in OpenNN::FinalSolutionsError.

Definition at line 307 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set ( DataSet new_data_set_pointer  )  [virtual]

This method sets all the member pointers to NULL, but the data set, which set to a given pointer. It also initializes all the rest of class members to their default values.

Parameters:
new_data_set_pointer Pointer to a data set object.

Definition at line 324 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set ( MathematicalModel new_mathematical_model_pointer  )  [virtual]

This method sets all the member pointers to NULL, but the mathematical model, which set to a given pointer. It also initializes all the rest of class members to their default values.

Parameters:
new_mathematical_model_pointer Pointer to a mathematical model object.

Reimplemented in OpenNN::FinalSolutionsError.

Definition at line 341 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set ( NeuralNetwork new_neural_network_pointer,
DataSet new_data_set_pointer 
) [virtual]

This method sets new neural network and data set pointers. It also sets the mathematical model and numerical differentiation pointers to NULL. Finally, it initializes all the rest of class members to their default values.

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

Definition at line 360 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set ( NeuralNetwork new_neural_network_pointer,
MathematicalModel new_mathematical_model_pointer 
) [virtual]

This method sets new neural network and mathematical model pointers. It also sets the data set and numerical differentiation pointers to NULL. Finally, it 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 data set object.

Reimplemented in OpenNN::FinalSolutionsError.

Definition at line 379 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set ( NeuralNetwork new_neural_network_pointer,
MathematicalModel new_mathematical_model_pointer,
DataSet new_data_set_pointer 
) [virtual]

This method sets new neural network, mathematical model and data set pointers. The numerical differentiation pointer is set to NULL. 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 mathematical model object.
new_data_set_pointer Pointer to a data set object.

Definition at line 399 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set ( const PerformanceTerm other_performance_term  )  [virtual]

This method sets to this performance term object the members of another performance term object.

Parameters:
other_performance_term Performance term to be copied.

Definition at line 415 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set_neural_network_pointer ( NeuralNetwork new_neural_network_pointer  )  [virtual]

This method sets a pointer to a neural network object which is to be associated to the performance term.

Parameters:
new_neural_network_pointer Pointer to a neural network object to be associated to the performance term.

Definition at line 437 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set_mathematical_model_pointer ( MathematicalModel new_mathematical_model_pointer  )  [virtual]

This method sets a new mathematical model on which the performance term is to be measured.

Reimplemented in OpenNN::FinalSolutionsError.

Definition at line 447 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set_data_set_pointer ( DataSet new_data_set_pointer  )  [virtual]

This method sets a new data set on which the performance term is to be measured.

Definition at line 457 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set_numerical_differentiation_pointer ( NumericalDifferentiation new_numerical_differentiation_pointer  ) 

This method sets a new numerical differentiation pointer in this performance term object.

Parameters:
new_numerical_differentiation_pointer Pointer to a numerical differentiation object.

Definition at line 468 of file performance_term.cpp.

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

This method sets the members of the performance term to their default values:

  • Display: true.

Reimplemented in OpenNN::FinalSolutionsError, OpenNN::IndependentParametersError, OpenNN::InverseSumSquaredError, OpenNN::MinkowskiError, OpenNN::NeuralParametersNorm, OpenNN::OutputsIntegrals, and OpenNN::SolutionsError.

Definition at line 481 of file performance_term.cpp.

void OpenNN::PerformanceTerm::set_display ( const bool &  new_display  ) 

This method sets a new display value. If it is set to true messages from this class are to be displayed on the screen; if it is set to false messages from this class are not to be displayed on the screen.

Parameters:
new_display Display value.

Definition at line 494 of file performance_term.cpp.

void OpenNN::PerformanceTerm::construct_numerical_differentiation ( void   ) 

This method constructs the numerical differentiation object which composes the performance term class.

Definition at line 504 of file performance_term.cpp.

void OpenNN::PerformanceTerm::delete_numerical_differentiation_pointer ( void   ) 

This method deletes the numerical differentiation object which composes the performance term class.

Definition at line 517 of file performance_term.cpp.

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

This method checks that there is a neural network associated to the performance term. If some of the above conditions is not hold, the method throws an exception.

Reimplemented in OpenNN::CrossEntropyError, OpenNN::FinalSolutionsError, OpenNN::IndependentParametersError, OpenNN::InverseSumSquaredError, OpenNN::MeanSquaredError, OpenNN::MinkowskiError, OpenNN::NeuralParametersNorm, OpenNN::NormalizedSquaredError, OpenNN::OutputsIntegrals, OpenNN::RootMeanSquaredError, OpenNN::SolutionsError, and OpenNN::SumSquaredError.

Definition at line 530 of file performance_term.cpp.

Vector< Vector< double > > OpenNN::PerformanceTerm::calculate_layers_delta ( const Vector< Vector< double > > &  layers_activation_derivative,
const Vector< double > &  output_objective_gradient 
) const

This method returns the delta vector for all the layers in the multilayer perceptron The format of this quantity is a vector of vectors.

Parameters:
layers_activation_derivative Forward propagation activation derivative.
output_objective_gradient Gradient of the outputs objective function.

Definition at line 553 of file performance_term.cpp.

Vector< Vector< double > > OpenNN::PerformanceTerm::calculate_layers_delta ( const Vector< Vector< double > > &  layers_activation_derivative,
const Vector< double > &  homogeneous_solution,
const Vector< double > &  output_objective_gradient 
) const

This method returns the delta vector for all the layers in the multilayer perceptron, when boundary conditions are imposed. The format of this quantity is a vector of vectors.

Parameters:
layers_activation_derivative Forward propagation activation derivative.
homogeneous_solution Homogeneous solution for calculating the conditioned outputs.
output_objective_gradient Gradient of the outputs objective function.

Definition at line 655 of file performance_term.cpp.

Matrix< Matrix< double > > OpenNN::PerformanceTerm::calculate_interlayers_Delta ( const Vector< Vector< double > > &  layers_activation_derivative,
const Vector< Vector< double > > &  layers_activation_second_derivative,
const Matrix< Matrix< double > > &  interlayers_combination_combination_Jacobian_form,
const Vector< double > &  output_objective_gradient,
const Matrix< double > &  output_objective_Hessian,
const Vector< Vector< double > > &  layers_delta 
) const

This method returns the second partial derivatives of the outputs objective function with respect to the combinations of two layers. That quantity is called interlayers Delta, and it is represented as a matrix of matrices.

Parameters:
layers_activation_derivative Activation derivatives of all layers in the multilayer perceptron
layers_activation_second_derivative Activation second derivatives of all layers in the multilayer perceptron
interlayers_combination_combination_Jacobian_form Matrix of matrices containing the partial derivatives of all layers combinations with respect to all layers combinations.
output_objective_gradient Gradient vector of the outputs objective function.
output_objective_Hessian Hessian matrix of the outputs objective function.
layers_delta Vector of vectors containing the partial derivatives of the outputs objective function with respect to the combinations of all layers.
Todo:

Definition at line 1001 of file performance_term.cpp.

Vector< double > OpenNN::PerformanceTerm::calculate_point_gradient ( const Vector< double > &  inputs,
const Vector< Vector< double > > &  layers_activation,
const Vector< Vector< double > > &  layers_delta 
) const

This method returns the gradient of the performance term function at some input point.

Parameters:
inputs Input vector.
layers_activation Activations of all layers in the multilayer perceptron
layers_delta Vector of vectors containing the partial derivatives of the outputs objective function with respect to all the combinations of all layers.

Definition at line 749 of file performance_term.cpp.

Vector< double > OpenNN::PerformanceTerm::calculate_point_gradient ( const Vector< Matrix< double > > &  layers_combination_parameters_Jacobian,
const Vector< Vector< double > > &  layers_delta 
) const

This method returns the gradient of the performance term function at some input point.

Parameters:
layers_combination_parameters_Jacobian 
layers_delta 

Definition at line 906 of file performance_term.cpp.

Matrix< double > OpenNN::PerformanceTerm::calculate_point_Hessian ( const Vector< Vector< double > > &  layers_activation_derivative,
const Vector< Vector< Vector< double > > > &  perceptrons_combination_parameters_gradient,
const Matrix< Matrix< double > > &  interlayers_combination_combination_Jacobian,
const Vector< Vector< double > > &  layers_delta,
const Matrix< Matrix< double > > &  interlayers_Delta 
) const

This method returns the Hessian of the performance term at some input.

Parameters:
layers_activation_derivative 
perceptrons_combination_parameters_gradient 
interlayers_combination_combination_Jacobian 
layers_delta 
interlayers_Delta 
Todo:

Definition at line 1130 of file performance_term.cpp.

virtual double OpenNN::PerformanceTerm::calculate_evaluation ( void   )  const [pure virtual]

virtual double OpenNN::PerformanceTerm::calculate_evaluation ( const Vector< double > &   )  const [inline, virtual]

virtual double OpenNN::PerformanceTerm::calculate_generalization_evaluation ( void   )  const [inline, virtual]

This method returns an evaluation of the performance term for generalization purposes.

Reimplemented in OpenNN::CrossEntropyError, OpenNN::InverseSumSquaredError, OpenNN::MeanSquaredError, OpenNN::MinkowskiError, OpenNN::NormalizedSquaredError, OpenNN::RootMeanSquaredError, and OpenNN::SumSquaredError.

Definition at line 258 of file performance_term.h.

Vector< double > OpenNN::PerformanceTerm::calculate_gradient ( void   )  const [virtual]

This method returns the objective function gradient vector for a neural network.

This method returns the default gradient vector of the objective term in the performance function definition.

Todo:

Reimplemented in OpenNN::CrossEntropyError, OpenNN::IndependentParametersError, OpenNN::MeanSquaredError, OpenNN::MinkowskiError, OpenNN::NeuralParametersNorm, OpenNN::NormalizedSquaredError, OpenNN::OutputsIntegrals, OpenNN::RootMeanSquaredError, and OpenNN::SumSquaredError.

Definition at line 1244 of file performance_term.cpp.

Matrix< double > OpenNN::PerformanceTerm::calculate_Hessian ( void   )  const [virtual]

Vector< double > OpenNN::PerformanceTerm::calculate_evaluation_terms ( void   )  const [virtual]

This method returns the evaluation of all the subterms composing the performance term.

Reimplemented in OpenNN::MeanSquaredError, OpenNN::NormalizedSquaredError, and OpenNN::SumSquaredError.

Definition at line 1301 of file performance_term.cpp.

Vector< double > OpenNN::PerformanceTerm::calculate_evaluation_terms ( const Vector< double > &   )  const [virtual]

This method returns the evaluation of all the subterms composing the performance term.

Reimplemented in OpenNN::MeanSquaredError, OpenNN::NormalizedSquaredError, and OpenNN::SumSquaredError.

Definition at line 1313 of file performance_term.cpp.

Matrix< double > OpenNN::PerformanceTerm::calculate_Jacobian_terms ( void   )  const [virtual]

This method returns the Jacobian matrix of the subterms composing the performance term.

Reimplemented in OpenNN::MeanSquaredError, OpenNN::NormalizedSquaredError, and OpenNN::SumSquaredError.

Definition at line 1325 of file performance_term.cpp.

PerformanceTerm::FirstOrderEvaluationTerms OpenNN::PerformanceTerm::calculate_first_order_evaluation_terms ( void   )  const [virtual]

This method returns the evaluation of all the subterms composing the performance term.

Reimplemented in OpenNN::SumSquaredError.

Definition at line 1337 of file performance_term.cpp.

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

std::string OpenNN::PerformanceTerm::write_information ( void   )  const [virtual]

This method returns a string with the default information of the performance term. It will be used by the training strategy to monitor the training process. By default this information is empty.

Reimplemented in OpenNN::FinalSolutionsError, OpenNN::IndependentParametersError, OpenNN::NeuralParametersNorm, and OpenNN::SolutionsError.

Definition at line 1361 of file performance_term.cpp.

std::string OpenNN::PerformanceTerm::to_string ( void   )  const [virtual]

This method returns the default string representation of a performance term.

Definition at line 1371 of file performance_term.cpp.

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

This method serializes a default performance term object into a XML element of the TinyXML library. See the OpenNN manual for more information about the format of this element.

Reimplemented in OpenNN::CrossEntropyError, OpenNN::FinalSolutionsError, OpenNN::IndependentParametersError, OpenNN::InverseSumSquaredError, OpenNN::MeanSquaredError, OpenNN::MinkowskiError, OpenNN::NeuralParametersNorm, OpenNN::NormalizedSquaredError, OpenNN::OutputsIntegrals, OpenNN::RootMeanSquaredError, OpenNN::SolutionsError, and OpenNN::SumSquaredError.

Definition at line 1387 of file performance_term.cpp.

void OpenNN::PerformanceTerm::from_XML ( TiXmlElement *  objective_term_element  )  [virtual]

This method loads a default performance term from a XML element.

Parameters:
objective_term_element Tiny XML element containing the performance term members.

Reimplemented in OpenNN::CrossEntropyError, OpenNN::FinalSolutionsError, OpenNN::IndependentParametersError, OpenNN::InverseSumSquaredError, OpenNN::MinkowskiError, OpenNN::NeuralParametersNorm, OpenNN::NormalizedSquaredError, OpenNN::OutputsIntegrals, OpenNN::RootMeanSquaredError, OpenNN::SolutionsError, and OpenNN::SumSquaredError.

Definition at line 1405 of file performance_term.cpp.

unsigned int OpenNN::PerformanceTerm::calculate_Kronecker_delta ( const unsigned int &  a,
const unsigned int &  b 
) const

This method returns the Knronecker delta of two integers a and b, which equals 1 if they are equal and 0 otherwise.

Parameters:
a First integer.
b Second integer.

Definition at line 1440 of file performance_term.cpp.


Member Data Documentation

Pointer to a multilayer perceptron object.

Definition at line 295 of file performance_term.h.

Pointer to a data set object.

Definition at line 299 of file performance_term.h.

Pointer to a mathematical model object.

Definition at line 303 of file performance_term.h.

Numerical differentiation object.

Definition at line 307 of file performance_term.h.

Display messages to screen.

Definition at line 311 of file performance_term.h.


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

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