OpenNN  2.2
Open Neural Networks Library
Classes | Public Member Functions | Private Attributes | List of all members
OpenNN::IncrementalOrder Class Reference

#include <incremental_order.h>

Inheritance diagram for OpenNN::IncrementalOrder:
OpenNN::OrderSelectionAlgorithm

Classes

struct  IncrementalOrderResults
 

Public Member Functions

 IncrementalOrder (void)
 
 IncrementalOrder (TrainingStrategy *)
 
 IncrementalOrder (const tinyxml2::XMLDocument &)
 
 IncrementalOrder (const std::string &)
 
virtual ~IncrementalOrder (void)
 
const size_t & get_step (void) const
 
const size_t & get_maximum_selection_failures (void) const
 
void set_default (void)
 
void set_step (const size_t &)
 
void set_maximum_selection_failures (const size_t &)
 
IncrementalOrderResultsperform_order_selection (void)
 
Matrix< std::string > to_string_matrix (void) const
 
tinyxml2::XMLDocument * to_XML (void) const
 
void from_XML (const tinyxml2::XMLDocument &)
 
void write_XML (tinyxml2::XMLPrinter &) const
 
void save (const std::string &) const
 
void load (const std::string &)
 
- Public Member Functions inherited from OpenNN::OrderSelectionAlgorithm
 OrderSelectionAlgorithm (void)
 
 OrderSelectionAlgorithm (TrainingStrategy *)
 
 OrderSelectionAlgorithm (const std::string &)
 
 OrderSelectionAlgorithm (const tinyxml2::XMLDocument &)
 
virtual ~OrderSelectionAlgorithm (void)
 
TrainingStrategyget_training_strategy_pointer (void) const
 
bool has_training_strategy (void) const
 
const size_t & get_maximum_order (void) const
 
const size_t & get_minimum_order (void) const
 
const size_t & get_trials_number (void) const
 
const bool & get_reserve_parameters_data (void) const
 
const bool & get_reserve_loss_data (void) const
 
const bool & get_reserve_selection_loss_data (void) const
 
const bool & get_reserve_minimal_parameters (void) const
 
const PerformanceCalculationMethodget_loss_calculation_method (void) const
 
const bool & get_display (void) const
 
const double & get_selection_loss_goal (void) const
 
const size_t & get_maximum_iterations_number (void) const
 
const double & get_maximum_time (void) const
 
const double & get_tolerance (void) const
 
std::string write_loss_calculation_method (void) const
 
void set_training_strategy_pointer (TrainingStrategy *)
 
void set_default (void)
 
void set_maximum_order (const size_t &)
 
void set_minimum_order (const size_t &)
 
void set_trials_number (const size_t &)
 
void set_reserve_parameters_data (const bool &)
 
void set_reserve_loss_data (const bool &)
 
void set_reserve_selection_loss_data (const bool &)
 
void set_reserve_minimal_parameters (const bool &)
 
void set_loss_calculation_method (const PerformanceCalculationMethod &)
 
void set_loss_calculation_method (const std::string &)
 
void set_display (const bool &)
 
void set_selection_loss_goal (const double &)
 
void set_maximum_iterations_number (const size_t &)
 
void set_maximum_time (const double &)
 
void set_tolerance (const double &)
 
Vector< double > perform_minimum_model_evaluation (const size_t &)
 
Vector< double > perform_maximum_model_evaluation (const size_t &)
 
Vector< double > perform_mean_model_evaluation (const size_t &)
 
Vector< double > get_final_losss (const TrainingStrategy::Results &) const
 
Vector< double > perform_model_evaluation (const size_t &)
 
Vector< double > get_parameters_order (const size_t &) const
 
void delete_selection_history (void)
 
void delete_loss_history (void)
 
void delete_parameters_history (void)
 
void check (void) const
 

Private Attributes

size_t step
 
size_t maximum_selection_failures
 

Additional Inherited Members

- Public Types inherited from OpenNN::OrderSelectionAlgorithm
enum  PerformanceCalculationMethod { Minimum, Maximum, Mean }
 
enum  StoppingCondition {
  MaximumTime, SelectionLossGoal, MaximumIterations, MaximumSelectionFailures,
  MinimumTemperature, AlgorithmFinished
}
 
- Protected Attributes inherited from OpenNN::OrderSelectionAlgorithm
TrainingStrategytraining_strategy_pointer
 
Vector< size_t > order_history
 
Vector< double > selection_loss_history
 
Vector< double > loss_history
 
Vector< Vector< double > > parameters_history
 
size_t minimum_order
 
size_t maximum_order
 
size_t trials_number
 
PerformanceCalculationMethod loss_calculation_method
 
bool reserve_parameters_data
 
bool reserve_loss_data
 
bool reserve_selection_loss_data
 
bool reserve_minimal_parameters
 
bool display
 
double selection_loss_goal
 
size_t maximum_iterations_number
 
double maximum_time
 
double tolerance
 

Detailed Description

This concrete class represents an incremental algorithm for the order selection of a neural network.

Definition at line 47 of file incremental_order.h.

Constructor & Destructor Documentation

◆ IncrementalOrder() [1/3]

OpenNN::IncrementalOrder::IncrementalOrder ( TrainingStrategy new_training_strategy_pointer)
explicit

Training strategy constructor.

Parameters
new_training_strategy_pointerPointer to a gradient descent object.

Definition at line 37 of file incremental_order.cpp.

◆ IncrementalOrder() [2/3]

OpenNN::IncrementalOrder::IncrementalOrder ( const tinyxml2::XMLDocument &  incremental_order_document)
explicit

XML constructor.

Parameters
incremental_order_documentPointer to a TinyXML document containing the incremental order data.

Definition at line 48 of file incremental_order.cpp.

◆ IncrementalOrder() [3/3]

OpenNN::IncrementalOrder::IncrementalOrder ( const std::string &  file_name)
explicit

File constructor.

Parameters
file_nameName of XML incremental order file.

Definition at line 59 of file incremental_order.cpp.

Member Function Documentation

◆ from_XML()

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

Deserializes a TinyXML document into this incremental order object.

Parameters
documentTinyXML document containing the member data.

Definition at line 839 of file incremental_order.cpp.

◆ load()

void OpenNN::IncrementalOrder::load ( const std::string &  file_name)

Loads a incremental order object from a XML-type file.

Parameters
file_nameName of incremental order XML-type file.

Definition at line 1160 of file incremental_order.cpp.

◆ save()

void OpenNN::IncrementalOrder::save ( const std::string &  file_name) const

Saves to a XML-type file the members of the incremental order object.

Parameters
file_nameName of incremental order XML-type file.

Definition at line 1145 of file incremental_order.cpp.

◆ set_maximum_selection_failures()

void OpenNN::IncrementalOrder::set_maximum_selection_failures ( const size_t &  new_maximum_loss_failures)

Sets the maximum selection failures for the Incremental order selection algorithm.

Parameters
new_maximum_loss_failuresMaximum number of selection failures in the Incremental order selection algorithm.

Definition at line 147 of file incremental_order.cpp.

◆ set_step()

void OpenNN::IncrementalOrder::set_step ( const size_t &  new_step)

Sets the number of the hidden perceptrons pointed in each iteration of the Incremental algorithm in the model order selection process.

Parameters
new_stepnumber of hidden perceptrons pointed.

Definition at line 112 of file incremental_order.cpp.

◆ to_XML()

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

Prints to the screen the incremental order parameters, the stopping criteria and other user stuff concerning the incremental order object.

Definition at line 512 of file incremental_order.cpp.

◆ write_XML()

void OpenNN::IncrementalOrder::write_XML ( tinyxml2::XMLPrinter &  file_stream) const

Serializes the incremental order object into a XML document of the TinyXML library without keep the DOM tree in memory. See the OpenNN manual for more information about the format of this document.

Definition at line 713 of file incremental_order.cpp.


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