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#Org.encog.neural.neat Classes and Interfaces - 29 results found.
NameDescriptionTypePackageFramework
FactorNEATGenomeThis factory is used to create NEATGenomes.Classorg.encog.neural.neatHeatonReasearch
MutateLinkWeightThis interface defines various ways that a NEAT network can have its link -----------------------------------------------------------------------------Interfaceorg.encog.neural.neat.training.opp.linksHeatonReasearch
MutatePerturbLinkWeightMutate weight links by perturbing their weights.Classorg.encog.neural.neat.training.opp.linksHeatonReasearch
MutateResetLinkWeightMutate weight links by reseting the weight to an entirely new value.Classorg.encog.neural.neat.training.opp.linksHeatonReasearch
NEATBaseGeneDefines a base class for NEAT genes.Classorg.encog.neural.neat.trainingHeatonReasearch
NEATCODECThis CODEC is used to create phenomes (NEATNetwork) objects using a genome (NEATGenome).Classorg.encog.neural.neatHeatonReasearch
NEATCrossoverCrossover is performed by mixing the link genes between the parents to produce an offspring.Classorg.encog.neural.neat.training.oppHeatonReasearch
NEATGenome ----------------------------------------------------------------------------- http://www.Classorg.encog.neural.neat.trainingHeatonReasearch
NEATGenomeFactoryThis interface defines additional methods defined to create NEAT genomes.Interfaceorg.encog.neural.neatHeatonReasearch
NEATInnovation previously tried with a neural network.Classorg.encog.neural.neat.trainingHeatonReasearch
NEATInnovationList NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks.Classorg.encog.neural.neat.trainingHeatonReasearch
NEATInnovationTypeenum NEATInnovationTypeThe type of NEAT innovation.Classorg.encog.neural.neat.trainingHeatonReasearch
NEATLink NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks.Classorg.encog.neural.neatHeatonReasearch
NEATLinkGene NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks.Classorg.encog.neural.neat.trainingHeatonReasearch
NEATMutateAddLinkMutates a NEAT genome by adding a link.Classorg.encog.neural.neat.training.oppHeatonReasearch
NEATMutateAddNodeMutate a genome by adding a new node.Classorg.encog.neural.neat.training.oppHeatonReasearch
NEATMutateRemoveLinkMutate a genome by removing a random link.Classorg.encog.neural.neat.training.oppHeatonReasearch
NEATMutateWeightsMutate the weights of a genome.Classorg.encog.neural.neat.training.oppHeatonReasearch
NEATMutationThis class represents a NEAT mutation.Classorg.encog.neural.neat.training.oppHeatonReasearch
NEATNetworkNEAT networks relieve the programmer of the need to define the hidden layer structure of the neural network.Classorg.encog.neural.neatHeatonReasearch
NEATNeuronGene NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks.Classorg.encog.neural.neat.trainingHeatonReasearch
NEATNeuronTypeThe types of neurons supported by NEAT.Classorg.encog.neural.neatHeatonReasearch
NEATPopulationA population for a NEAT or HyperNEAT system.Classorg.encog.neural.neatHeatonReasearch
NEATUtilNEAT does not make use of a special trainer.Classorg.encog.neural.neatHeatonReasearch
OriginalNEATSpeciationThe original NEAT Speciation Strategy.Classorg.encog.neural.neat.training.speciesHeatonReasearch
PersistNEATPopulationPersist a NEAT or HyperNEAT network.Classorg.encog.neural.neatHeatonReasearch
SelectFixedSelect a fixed number of link genes.Classorg.encog.neural.neat.training.opp.linksHeatonReasearch
SelectLinksThis interface defines ways that NEAT links can be chosen for mutation.Interfaceorg.encog.neural.neat.training.opp.linksHeatonReasearch
SelectProportionSelect a random proportion of links to mutate.Classorg.encog.neural.neat.training.opp.linksHeatonReasearch