14 #ifndef __SUMSQUAREDERROR_H__
15 #define __SUMSQUAREDERROR_H__
28 #include "performance_term.h"
33 #include "../tinyxml2/tinyxml2.h"
83 void check(
void)
const;
118 tinyxml2::XMLDocument*
to_XML(
void)
const;
120 void from_XML(
const tinyxml2::XMLDocument&);
double calculate_performance(void) const
Returns the performance value of a neural network according to the sum squared error on a data set...
double calculate_generalization_performance(void) const
Returns the sum squared error of the neural network measured on the generalization instances of the d...
tinyxml2::XMLDocument * to_XML(void) const
Returns a representation of the sum squared error object, in XML format.
virtual ~SumSquaredError(void)
Destructor.
Vector< double > calculate_gradient(void) const
Matrix< double > calculate_Hessian(void) const
Matrix< double > calculate_terms_Jacobian(void) const
void from_XML(const tinyxml2::XMLDocument &)
Vector< double > calculate_terms(void) const
Calculates the squared error terms for each instance, and returns it in a vector of size the number t...
PerformanceTerm::FirstOrderTerms calculate_first_order_terms(void) const
std::string write_performance_term_type(void) const
Returns a string with the name of the sum squared error performance type, "SUM_SQUARED_ERROR".
Vector< double > calculate_squared_errors(void) const
Returns the squared errors of the training instances.