C# Class Encog.Neural.NEAT.Training.NEATTraining

Implements NEAT genetic training. NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks. It was developed by Ken Stanley while at The University of Texas at Austin. http://www.cs.ucf.edu/~kstanley/

Inheritance: Encog.ML.Genetic.GeneticAlgorithm, IMLTrain

Afficher le fichier Open project: encog/encog-silverlight-core Class Usage Examples

Méthodes publiques

Méthode	Description
AddNeuronID ( long nodeID, IList vec ) : void	Add the specified neuron id.
AddStrategy ( IStrategy strategy ) : void
AdjustCompatibilityThreshold ( ) : void	Adjust the compatibility threshold.
AdjustSpeciesScore ( ) : void	Adjust each species score.
Crossover ( NEATGenome mom, NEATGenome dad ) : NEATGenome	Perform a cross over.
FinishTraining ( ) : void
Iteration ( ) : void	Perform one training iteration.
Iteration ( int count ) : void
NEATTraining ( ICalculateScore calculateScore, IPopulation population ) : System	Construct neat training with an existing population.
NEATTraining ( ICalculateScore calculateScore, int inputCount, int outputCount, int populationSize ) : System	Construct a neat trainer with a new population. The new population is created from the specified parameters.
Pause ( ) : TrainingContinuation
ResetAndKill ( ) : void	Reset counts and kill genomes with worse scores.
Resume ( TrainingContinuation state ) : void
SortAndRecord ( ) : void	Sort the genomes.
SpeciateAndCalculateSpawnLevels ( ) : void	Determine the species.
TournamentSelection ( int numComparisons ) : NEATGenome	Select a gene using a tournament.

Private Methods

Méthode	Description
Init ( ) : void	Init the training.

Method Details

AddNeuronID() public méthode

Add the specified neuron id.

public AddNeuronID ( long nodeID, IList vec ) : void
nodeID	long	The neuron to add.
vec	IList	The list to add to.
Résultat	void

AddStrategy() public méthode

public AddStrategy ( IStrategy strategy ) : void
strategy	IStrategy
Résultat	void

AdjustCompatibilityThreshold() public méthode

Adjust the compatibility threshold.

public AdjustCompatibilityThreshold ( ) : void
Résultat	void

AdjustSpeciesScore() public méthode

Adjust each species score.

public AdjustSpeciesScore ( ) : void
Résultat	void

Crossover() public méthode

Perform a cross over.

public Crossover ( NEATGenome mom, NEATGenome dad ) : NEATGenome
mom	NEATGenome	The mother genome.
dad	NEATGenome	The father genome.
Résultat	NEATGenome

FinishTraining() public méthode

public FinishTraining ( ) : void
Résultat	void

Iteration() public méthode

Perform one training iteration.

public Iteration ( ) : void
Résultat	void

Iteration() public méthode

public Iteration ( int count ) : void
count	int
Résultat	void

NEATTraining() public méthode

Construct neat training with an existing population.

public NEATTraining ( ICalculateScore calculateScore, IPopulation population ) : System
calculateScore	ICalculateScore	The score object to use.
population	IPopulation	The population to use.
Résultat	System

NEATTraining() public méthode

Construct a neat trainer with a new population. The new population is created from the specified parameters.

public NEATTraining ( ICalculateScore calculateScore, int inputCount, int outputCount, int populationSize ) : System
calculateScore	ICalculateScore	The score calculation object.
inputCount	int	The input neuron count.
outputCount	int	The output neuron count.
populationSize	int	The population size.
Résultat	System

Pause() public méthode

public Pause ( ) : TrainingContinuation
Résultat	Encog.Neural.Networks.Training.Propagation.TrainingContinuation

ResetAndKill() public méthode

Reset counts and kill genomes with worse scores.

public ResetAndKill ( ) : void
Résultat	void

Resume() public méthode

public Resume ( TrainingContinuation state ) : void
state	Encog.Neural.Networks.Training.Propagation.TrainingContinuation
Résultat	void

SortAndRecord() public méthode

Sort the genomes.

public SortAndRecord ( ) : void
Résultat	void

SpeciateAndCalculateSpawnLevels() public méthode

Determine the species.

public SpeciateAndCalculateSpawnLevels ( ) : void
Résultat	void

TournamentSelection() public méthode

Select a gene using a tournament.

public TournamentSelection ( int numComparisons ) : NEATGenome
numComparisons	int	The number of compares to do.
Résultat	NEATGenome