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

Mostrar archivo Open project: encog/encog-silverlight-core Class Usage Examples

Public Methods

Method	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

Method	Description
Init ( ) : void	Init the training.

Method Details

AddNeuronID() public method

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.
return	void

AddStrategy() public method

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

AdjustCompatibilityThreshold() public method

Adjust the compatibility threshold.

public AdjustCompatibilityThreshold ( ) : void
return	void

AdjustSpeciesScore() public method

Adjust each species score.

public AdjustSpeciesScore ( ) : void
return	void

Crossover() public method

Perform a cross over.

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

FinishTraining() public method

public FinishTraining ( ) : void
return	void

Iteration() public method

Perform one training iteration.

public Iteration ( ) : void
return	void

Iteration() public method

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

NEATTraining() public method

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.
return	System

NEATTraining() public method

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.
return	System

Pause() public method

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

ResetAndKill() public method

Reset counts and kill genomes with worse scores.

public ResetAndKill ( ) : void
return	void

Resume() public method

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

SortAndRecord() public method

Sort the genomes.

public SortAndRecord ( ) : void
return	void

SpeciateAndCalculateSpawnLevels() public method

Determine the species.

public SpeciateAndCalculateSpawnLevels ( ) : void
return	void

TournamentSelection() public method

Select a gene using a tournament.

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