Method | Description | |
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Iteration ( ) : void |
Perform one training iteration.
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NeuralGeneticAlgorithm ( BasicNetwork network, IRandomizer randomizer, ICalculateScore calculateScore, int populationSize, double mutationPercent, double percentToMate ) : Encog.MathUtil.Randomize |
Construct a neural genetic algorithm.
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Pause ( ) : TrainingContinuation | ||
Resume ( TrainingContinuation state ) : void |
public NeuralGeneticAlgorithm ( BasicNetwork network, IRandomizer randomizer, ICalculateScore calculateScore, int populationSize, double mutationPercent, double percentToMate ) : Encog.MathUtil.Randomize | ||
network | BasicNetwork | The network to base this on. |
randomizer | IRandomizer | The randomizer used to create this initial population. |
calculateScore | ICalculateScore | The score calculation object. |
populationSize | int | The population size. |
mutationPercent | double | The percent of offspring to mutate. |
percentToMate | double | The percent of the population allowed to mate. |
return | Encog.MathUtil.Randomize |
public final Pause ( ) : TrainingContinuation | ||
return | TrainingContinuation |
public final Resume ( TrainingContinuation state ) : void | ||
state | TrainingContinuation | |
return | void |