opennn::GeneticAlgorithm Class Reference

Selects the optimal subset of input features using an evolutionary genetic algorithm. More...

#include <genetic_algorithm.h>

Inheritance diagram for opennn::GeneticAlgorithm:

Public Member Functions
	GeneticAlgorithm (TrainingStrategy *=nullptr)
	Constructs the algorithm bound to an optional training strategy.
Index	get_individuals_number () const
Index	get_genes_number () const
void	set_default ()
	Restores default population size, mutation rate, elitism and other parameters.
Index	get_minimum_inputs_number () const override
	Returns the minimum number of input variables that the algorithm may select.
Index	get_maximum_inputs_number () const override
	Returns the maximum number of input variables that the algorithm may select.
void	set_minimum_inputs_number (const Index new_minimum)
void	set_maximum_inputs_number (const Index)
	Sets the upper bound on the number of selected inputs.
void	set_individuals_number (const Index new_individuals_number=4)
	Sets the size of the population evolved by the algorithm.
void	set_initialization_method (string method)
void	set_mutation_rate (const float rate)
void	set_elitism_size (const Index size)
InputsSelectionResults	perform_input_selection () override
	Runs the genetic algorithm until the stopping criterion is met.
void	from_JSON (const JsonDocument &) override
	Loads algorithm configuration from a JSON document.
void	to_JSON (JsonWriter &) const override
	Writes algorithm configuration to a JSON writer.
Public Member Functions inherited from opennn::InputsSelection
	InputsSelection (TrainingStrategy *=nullptr)
	Constructs the algorithm bound to an optional training strategy.
virtual	~InputsSelection ()=default
const TrainingStrategy *	get_training_strategy () const
bool	has_training_strategy () const
bool	get_display () const
void	set (TrainingStrategy *new_training_strategy)
void	set_trials_number (const Index new_trials_number)
void	set_display (bool new_display)
void	set_validation_error_goal (const float new_validation_error_goal)
void	set_maximum_epochs (const Index new_maximum_epochs)
void	set_maximum_validation_failures (const Index new_maximum_validation_failures)
void	set_maximum_time (const float new_maximum_time)
void	check () const
	Verifies that the training strategy and its dependencies are valid for inputs selection.
string	get_name () const
void	save (const filesystem::path &) const
	Saves the algorithm configuration to disk.
void	load (const filesystem::path &)
	Loads the algorithm configuration from disk.
virtual void	print () const
	Prints a human-readable description of the algorithm to stdout.

Additional Inherited Members
Public Types inherited from opennn::InputsSelection
enum class	StoppingCondition {   MaximumTime , SelectionErrorGoal , MaximumInputs , MaximumEpochs ,   MaximumSelectionFailures }
	Reasons the inputs selection loop may terminate. More...
Protected Attributes inherited from opennn::InputsSelection
TrainingStrategy *	training_strategy = nullptr
Index	trials_number = 1
bool	display = true
float	validation_error_goal
Index	maximum_epochs
Index	maximum_validation_failures = 100
float	maximum_time
string	name

Detailed Description

Selects the optimal subset of input features using an evolutionary genetic algorithm.

Constructor & Destructor Documentation

GeneticAlgorithm()

opennn::GeneticAlgorithm::GeneticAlgorithm

(

TrainingStrategy *

= nullptr

)

Constructs the algorithm bound to an optional training strategy.

Member Function Documentation

from_JSON()

void opennn::GeneticAlgorithm::from_JSON ( const JsonDocument & )

overridevirtual

Loads algorithm configuration from a JSON document.

Implements opennn::InputsSelection.

get_genes_number()

Index opennn::GeneticAlgorithm::get_genes_number ( ) const

inline

get_individuals_number()

Index opennn::GeneticAlgorithm::get_individuals_number ( ) const

inline

get_maximum_inputs_number()

Index opennn::GeneticAlgorithm::get_maximum_inputs_number ( ) const

inlineoverridevirtual

Returns the maximum number of input variables that the algorithm may select.

Implements opennn::InputsSelection.

get_minimum_inputs_number()

Index opennn::GeneticAlgorithm::get_minimum_inputs_number ( ) const

inlineoverridevirtual

Returns the minimum number of input variables that the algorithm may select.

Implements opennn::InputsSelection.

perform_input_selection()

InputsSelectionResults opennn::GeneticAlgorithm::perform_input_selection ( )

overridevirtual

Runs the genetic algorithm until the stopping criterion is met.

Returns

Selection results including the best individual's inputs and error history.

Implements opennn::InputsSelection.

set_default()

void opennn::GeneticAlgorithm::set_default

(

)

Restores default population size, mutation rate, elitism and other parameters.

set_elitism_size()

void opennn::GeneticAlgorithm::set_elitism_size ( const Index size )

inline

set_individuals_number()

void opennn::GeneticAlgorithm::set_individuals_number

(

const Index

new_individuals_number = 4

)

Sets the size of the population evolved by the algorithm.

set_initialization_method()

void opennn::GeneticAlgorithm::set_initialization_method ( string method )

inline

set_maximum_inputs_number()

void opennn::GeneticAlgorithm::set_maximum_inputs_number

(

const Index

)

Sets the upper bound on the number of selected inputs.

set_minimum_inputs_number()

void opennn::GeneticAlgorithm::set_minimum_inputs_number ( const Index new_minimum )

inline

set_mutation_rate()

void opennn::GeneticAlgorithm::set_mutation_rate ( const float rate )

inline

to_JSON()

void opennn::GeneticAlgorithm::to_JSON ( JsonWriter & ) const

overridevirtual

Writes algorithm configuration to a JSON writer.

Implements opennn::InputsSelection.