OpenNN::CrossEntropyError Class Reference

#include <cross_entropy_error.h>

Inheritance diagram for OpenNN::CrossEntropyError:

Public Member Functions
	CrossEntropyError (void)
	CrossEntropyError (NeuralNetwork *)
	CrossEntropyError (DataSet *)
	CrossEntropyError (NeuralNetwork *, DataSet *)
	CrossEntropyError (const tinyxml2::XMLDocument &)
	CrossEntropyError (const CrossEntropyError &)
virtual	~CrossEntropyError (void)
CrossEntropyError &	operator= (const CrossEntropyError &)
bool	operator== (const CrossEntropyError &) const
void	check (void) const
double	calculate_performance (void) const
double	calculate_performance (const Vector< double > &) const
double	calculate_minimum_performance (void)
double	calculate_generalization_performance (void) const
double	calculate_minimum_generalization_performance (void)
Vector< double >	calculate_gradient (void) const
Matrix< double >	calculate_Hessian (void) const
std::string	write_performance_term_type (void) const
tinyxml2::XMLDocument *	to_XML (void) const
void	from_XML (const tinyxml2::XMLDocument &)
Public Member Functions inherited from OpenNN::PerformanceTerm
	PerformanceTerm (void)
	PerformanceTerm (NeuralNetwork *)
	PerformanceTerm (DataSet *)
	PerformanceTerm (MathematicalModel *)
	PerformanceTerm (NeuralNetwork *, DataSet *)
	PerformanceTerm (NeuralNetwork *, MathematicalModel *)
	PerformanceTerm (NeuralNetwork *, MathematicalModel *, DataSet *)
	PerformanceTerm (const tinyxml2::XMLDocument &)
	PerformanceTerm (const PerformanceTerm &)
virtual	~PerformanceTerm (void)
virtual PerformanceTerm &	operator= (const PerformanceTerm &)
virtual bool	operator== (const PerformanceTerm &) const
NeuralNetwork *	get_neural_network_pointer (void) const
MathematicalModel *	get_mathemtaical_model_pointer (void) const
DataSet *	get_data_set_pointer (void) const
NumericalDifferentiation *	get_numerical_differentiation_pointer (void) const
const bool &	get_display (void) const
bool	has_neural_network (void) const
bool	has_mathematical_model (void) const
bool	has_data_set (void) const
bool	has_numerical_differentiation (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 *)
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)
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 Vector< double >	calculate_gradient (const Vector< double > &) const
virtual Matrix< double >	calculate_Hessian (const Vector< double > &) const
virtual Vector< double >	calculate_terms (void) const
virtual Vector< double >	calculate_terms (const Vector< double > &) const
virtual Matrix< double >	calculate_terms_Jacobian (void) const
virtual PerformanceTerm::FirstOrderTerms	calculate_first_order_terms (void) const
virtual std::string	write_information (void) const
virtual std::string	to_string (void) const
size_t	calculate_Kronecker_delta (const size_t &, const size_t &) const

Additional Inherited Members
Protected Attributes inherited from OpenNN::PerformanceTerm
NeuralNetwork *	neural_network_pointer
DataSet *	data_set_pointer
MathematicalModel *	mathematical_model_pointer
NumericalDifferentiation *	numerical_differentiation_pointer
bool	display

Detailed Description

This class represents the cross entropy performance term. This functional is used in pattern recognition problems.

Definition at line 39 of file cross_entropy_error.h.

Constructor & Destructor Documentation

OpenNN::CrossEntropyError::CrossEntropyError ( void  )

explicit

Default constructor. It creates a default cross entropy error performance term object, which is not associated to any neural network and not measured on any data set. It also initializes all the rest of class members to their default values.

Definition at line 28 of file cross_entropy_error.cpp.

OpenNN::CrossEntropyError::CrossEntropyError ( NeuralNetwork *  new_neural_network_pointer )

explicit

Neural network constructor. It creates a cross entropy error performance term associated to a neural network but not measured on any 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 40 of file cross_entropy_error.cpp.

OpenNN::CrossEntropyError::CrossEntropyError ( DataSet *  new_data_set_pointer )

explicit

Data set constructor. It creates a cross entropy error not associated to any neural network but to be measured on a data set object. 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 53 of file cross_entropy_error.cpp.

OpenNN::CrossEntropyError::CrossEntropyError ( NeuralNetwork *  new_neural_network_pointer, DataSet *  new_data_set_pointer  )

explicit

Neural network and data set constructor. It creates a cross entropy error performance term object associated to a neural network and measured 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.
new_data_set_pointer	Pointer to a data set object.

Definition at line 67 of file cross_entropy_error.cpp.

OpenNN::CrossEntropyError::CrossEntropyError ( const tinyxml2::XMLDocument &  sum_squared_error_document )

explicit

XML constructor. It creates a cross entropy error not associated to any neural network and not measured on any data set. It also sets all the rest of class members from a TinyXML document->

Parameters

sum_squared_error_document

XML document with the class members.

Definition at line 80 of file cross_entropy_error.cpp.

OpenNN::CrossEntropyError::CrossEntropyError

(

const CrossEntropyError &

new_cross_entropy_error

)

Copy constructor. It creates a cross entropy error not associated to any neural network and not measured on any data set. It also sets all the rest of class members from another sum squared error object.

Parameters

new_cross_entropy_error

Object to be copied.

Definition at line 93 of file cross_entropy_error.cpp.

Member Function Documentation

double OpenNN::CrossEntropyError::calculate_generalization_performance ( void  ) const

virtual

Returns the cross entropy error of the neural network measured on the generalization instances of the data set.

Todo:

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 370 of file cross_entropy_error.cpp.

Vector< double > OpenNN::CrossEntropyError::calculate_gradient ( void  ) const

virtual

Returns the cross entropy error gradient of a neural network on a data set. It uses the error back-propagation method.

Todo:

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 466 of file cross_entropy_error.cpp.

Matrix< double > OpenNN::CrossEntropyError::calculate_Hessian ( void  ) const

virtual

Todo:

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 620 of file cross_entropy_error.cpp.

double OpenNN::CrossEntropyError::calculate_minimum_generalization_performance

(

void

)

Returns the minimum achieveable cross entropy for the generalization data.

Todo:

Definition at line 454 of file cross_entropy_error.cpp.

double OpenNN::CrossEntropyError::calculate_minimum_performance

(

void

)

Returns the minimum achieveable cross entropy for the training data.

Todo:

Definition at line 359 of file cross_entropy_error.cpp.

double OpenNN::CrossEntropyError::calculate_performance ( void  ) const

virtual

Todo:

Implements OpenNN::PerformanceTerm.

Definition at line 268 of file cross_entropy_error.cpp.

void OpenNN::CrossEntropyError::check ( void  ) const

virtual

Checks that there are a neural network and a data set associated to the cross entropy error, and that the numbers of inputs and outputs in the neural network are equal to the numbers of inputs and targets in the data set.

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 157 of file cross_entropy_error.cpp.

void OpenNN::CrossEntropyError::from_XML ( const tinyxml2::XMLDocument &  document )

virtual

Deserializes a TinyXML document into this cross entropy object.

Parameters

document

TinyXML document containing the member data.

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 677 of file cross_entropy_error.cpp.

CrossEntropyError & OpenNN::CrossEntropyError::operator=

(

const CrossEntropyError &

other_cross_entropy_error

)

Assignment operator.

Parameters

other_cross_entropy_error

Object to be copied.

Definition at line 114 of file cross_entropy_error.cpp.

bool OpenNN::CrossEntropyError::operator==

(

const CrossEntropyError &

other_cross_entropy_error

)

const

Equal to operator. If compares this object with another object of the same class, and returns true if they are equal, and false otherwise.

Parameters

other_cross_entropy_error

Object to be compared with.

Definition at line 133 of file cross_entropy_error.cpp.

tinyxml2::XMLDocument * OpenNN::CrossEntropyError::to_XML ( void  ) const

virtual

Serializes the cross entropy error object into a XML document of the TinyXML library. See the OpenNN manual for more information about the format of this document->

Reimplemented from OpenNN::PerformanceTerm.

Definition at line 643 of file cross_entropy_error.cpp.

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

• cross_entropy_error.h
• cross_entropy_error.cpp