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