Search Java Classes and Packages
#Org.encog.neural Classes and Interfaces - 177 results found.
| Name | Description | Type | Package | Framework |
| AbstractPNN | Abstract class to build PNN networks upon. | Class | org.encog.neural.pnn | HeatonReasearch |
| ADALINEPattern | Construct an ADALINE neural network. | Class | org.encog.neural.pattern | HeatonReasearch |
| AnalyzeNetwork | Allows the weights and bias values of the neural network to be analyzed. | Class | org.encog.neural.networks.structure | HeatonReasearch |
| ART | Adaptive Resonance Theory (ART) is a form of neural network developed by Stephen Grossberg and Gail Carpenter. | Class | org.encog.neural.art | HeatonReasearch |
| ART1 | recognize bipolar patterns as it is presented data. | Class | org.encog.neural.art | HeatonReasearch |
| ART1Pattern | Pattern to create an ART-1 neural network. | Class | org.encog.neural.pattern | HeatonReasearch |
| ATanErrorFunction | An ATan based error function. | Class | org.encog.neural.error | HeatonReasearch |
| Backpropagation | This class implements a backpropagation training algorithm for feed forward neural networks. | Class | org.encog.neural.networks.training.propagation.back | HeatonReasearch |
| BAM | Bidirectional associative memory (BAM) is a type of neural network developed by Bart Kosko in 1988. | Class | org.encog.neural.bam | HeatonReasearch |
| BAMPattern | Construct a Bidirectional Access Memory (BAM) neural network. | Class | org.encog.neural.pattern | HeatonReasearch |
| BasicActivationSummation | Provides a basic implementation of an input summation. | Class | org.encog.neural.freeform.basic | HeatonReasearch |
| BasicActivationSummationFactory | A factory to create BasicFactivationSUmmation objects. | Class | org.encog.neural.freeform.basic | HeatonReasearch |
| BasicFreeformConnection | A basic freeform connection. | Class | org.encog.neural.freeform.basic | HeatonReasearch |
| BasicFreeformConnectionFactory | Class | org.encog.neural.freeform.basic | HeatonReasearch | |
| BasicFreeformLayer | Class | org.encog.neural.freeform.basic | HeatonReasearch | |
| BasicFreeformLayerFactory | A factory that creates BasicFreeformLayer objects. | Class | org.encog.neural.freeform.basic | HeatonReasearch |
| BasicFreeformNeuron | This class provides a basic implementation of a freeform neuron. | Class | org.encog.neural.freeform.basic | HeatonReasearch |
| BasicFreeformNeuronFactory | A factory to create BasicFreeformNeuron objects. | Class | org.encog.neural.freeform.basic | HeatonReasearch |
| BasicLayer | Basic functionality that most of the neural layers require. | Class | org.encog.neural.networks.layers | HeatonReasearch |
| BasicNetwork | This class implements a neural network. | Class | org.encog.neural.networks | HeatonReasearch |
| BasicNeuralData | This is an alias class for Encog 2. | Class | org.encog.neural.data.basic | HeatonReasearch |
| BasicNeuralDataPair | This is an alias class for Encog 2. | Class | org.encog.neural.data.basic | HeatonReasearch |
| BasicNeuralDataSet | This is an alias class for Encog 2. | Class | org.encog.neural.data.basic | HeatonReasearch |
| BasicPNN | This class implements either a: Probabilistic Neural Network (PNN) | Class | org.encog.neural.pnn | HeatonReasearch |
| BasicTrainSOM | This class implements competitive training, which would be used in a winner-take-all neural network, such as the self organizing map (SOM). | Class | org.encog.neural.som.training.basic | HeatonReasearch |
| BatchSize | The batch size. | Interface | org.encog.neural.networks.training | HeatonReasearch |
| BestMatchingUnit | The "Best Matching Unit" or BMU is a very important concept in the training for a SOM. | Class | org.encog.neural.som.training.basic | HeatonReasearch |
| BoltzmannMachine | Class | org.encog.neural.thermal | HeatonReasearch | |
| BoltzmannPattern | Pattern to create a Boltzmann machine. | Class | org.encog.neural.pattern | HeatonReasearch |
| BPROPJob | A training definition for BPROP training. | Class | org.encog.neural.networks.training.concurrent.jobs | HeatonReasearch |
| CalculationCriteria | Interface | org.encog.neural.networks.training.pnn | HeatonReasearch | |
| ConcurrentTrainingManager | Concurrent training manager. | Class | org.encog.neural.networks.training.concurrent | HeatonReasearch |
| ConcurrentTrainingPerformer | Performers actually perform the training. | Interface | org.encog.neural.networks.training.concurrent.performers | HeatonReasearch |
| ConcurrentTrainingPerformerCPU | This performer allows jobs to be performed by the CPU. | Class | org.encog.neural.networks.training.concurrent.performers | HeatonReasearch |
| ConnectionTask | Interface | org.encog.neural.freeform.task | HeatonReasearch | |
| ContainsFlat | Interface | org.encog.neural.networks | HeatonReasearch | |
| CPN | Counterpropagation Neural Networks (CPN) were developed by Professor Robert Hecht-Nielsen in 1987. | Class | org.encog.neural.cpn | HeatonReasearch |
| CPNPattern | Pattern that creates a CPN neural network. | Class | org.encog.neural.pattern | HeatonReasearch |
| CrossTraining | Base class for cross training trainers. | Class | org.encog.neural.networks.training.cross | HeatonReasearch |
| CrossValidationKFold | Train using K-Fold cross validation. | Class | org.encog.neural.networks.training.cross | HeatonReasearch |
| DeriveMinimum | This class determines optimal values for multiple sigmas in a PNN kernel. | Class | org.encog.neural.networks.training.pnn | HeatonReasearch |
| ElmanPattern | This class is used to generate an Elman style recurrent neural network. | Class | org.encog.neural.pattern | HeatonReasearch |
| ErrorFunction | An error function. | Interface | org.encog.neural.error | HeatonReasearch |
| FactorHyperNEATGenome | Create a Genome for use with HyperNEAT. | Class | org.encog.neural.hyperneat | HeatonReasearch |
| FactorNEATGenome | This factory is used to create NEATGenomes. | Class | org.encog.neural.neat | HeatonReasearch |
| FeedForwardPattern | Used to create feedforward neural networks. | Class | org.encog.neural.pattern | HeatonReasearch |
| FlatLayer | Used to configure a flat layer. | Class | org.encog.neural.flat | HeatonReasearch |
| FlatNetwork | meant to be a very highly efficient feedforward, or simple recurrent, neural network. | Class | org.encog.neural.flat | HeatonReasearch |
| FlatNetworkRBF | A flat network designed to handle an RBF. | Class | org.encog.neural.flat | HeatonReasearch |
| FreeformBackPropagation | Perform backpropagation for a freeform neural network. | Class | org.encog.neural.freeform.training | HeatonReasearch |
| FreeformConnection | Defines a freeform connection between neurons. | Interface | org.encog.neural.freeform | HeatonReasearch |
| FreeformConnectionFactory | A factory that creates connections. | Interface | org.encog.neural.freeform.factory | HeatonReasearch |
| FreeformContextNeuron | Defines a freeform context neuron. | Class | org.encog.neural.freeform | HeatonReasearch |
| FreeformLayer | Defines a freeform layer. | Interface | org.encog.neural.freeform | HeatonReasearch |
| FreeformLayerFactory | A factory that creates layers. | Interface | org.encog.neural.freeform.factory | HeatonReasearch |
| FreeformNetwork | much more advanced structures than the flat networks that the Encog BasicNetwork implements. | Class | org.encog.neural.freeform | HeatonReasearch |
| FreeformNetworkError | Freeform neural network error. | Class | org.encog.neural.freeform | HeatonReasearch |
| FreeformNeuron | This interface defines a freeform neuron. | Interface | org.encog.neural.freeform | HeatonReasearch |
| FreeformNeuronFactory | A factory that creates neurons. | Interface | org.encog.neural.freeform.factory | HeatonReasearch |
| FreeformPropagationTraining | Provides basic propagation functions to other trainers. | Class | org.encog.neural.freeform.training | HeatonReasearch |
| FreeformResilientPropagation | Class | org.encog.neural.freeform.training | HeatonReasearch | |
| GlobalMinimumSearch | Search sigma's for a global minimum. | Class | org.encog.neural.networks.training.pnn | HeatonReasearch |
| GradientWorker | Worker class for the mulithreaded training of flat networks. | Class | org.encog.neural.networks.training.propagation | HeatonReasearch |
| HiddenLayerParams | Specifies the minimum and maximum neuron counts for a layer. | Class | org.encog.neural.prune | HeatonReasearch |
| HopfieldNetwork | Class | org.encog.neural.thermal | HeatonReasearch | |
| HopfieldPattern | Create a Hopfield pattern. | Class | org.encog.neural.pattern | HeatonReasearch |
| HyperNEATCODEC | Class | org.encog.neural.hyperneat | HeatonReasearch | |
| HyperNEATGenome | Class | org.encog.neural.hyperneat | HeatonReasearch | |
| InputSummation | Specifies how the inputs to a neuron are to be summed. | Interface | org.encog.neural.freeform | HeatonReasearch |
| InputSummationFactory | Factory that creates input summations. | Interface | org.encog.neural.freeform.factory | HeatonReasearch |
| JordanPattern | This class is used to generate an Jordan style recurrent neural network. | Class | org.encog.neural.pattern | HeatonReasearch |
| Layer | This interface defines all necessary methods for a neural network layer. | Interface | org.encog.neural.networks.layers | HeatonReasearch |
| LearningRate | Specifies that a training algorithm has the concept of a learning rate. | Interface | org.encog.neural.networks.training | HeatonReasearch |
| LevenbergMarquardtTraining | Trains a neural network using a Levenberg Marquardt algorithm (LMA). | Class | org.encog.neural.networks.training.lma | HeatonReasearch |
| LinearErrorFunction | The standard linear error function, simply returns the difference between the actual and ideal. | Class | org.encog.neural.error | HeatonReasearch |
| ManhattanPropagation | One problem that the backpropagation technique has is that the magnitude of the partial derivative may be calculated too large or too small. | Class | org.encog.neural.networks.training.propagation.manhattan | HeatonReasearch |
| Momentum | Specifies that a training algorithm has the concept of a momentum. | Interface | org.encog.neural.networks.training | HeatonReasearch |
| MutateLinkWeight | This interface defines various ways that a NEAT network can have its link ----------------------------------------------------------------------------- | Interface | org.encog.neural.neat.training.opp.links | HeatonReasearch |
| MutatePerturbLinkWeight | Mutate weight links by perturbing their weights. | Class | org.encog.neural.neat.training.opp.links | HeatonReasearch |
| MutateResetLinkWeight | Mutate weight links by reseting the weight to an entirely new value. | Class | org.encog.neural.neat.training.opp.links | HeatonReasearch |
| NEATBaseGene | Defines a base class for NEAT genes. | Class | org.encog.neural.neat.training | HeatonReasearch |
| NEATCODEC | This CODEC is used to create phenomes (NEATNetwork) objects using a genome (NEATGenome). | Class | org.encog.neural.neat | HeatonReasearch |
| NEATCrossover | Crossover is performed by mixing the link genes between the parents to produce an offspring. | Class | org.encog.neural.neat.training.opp | HeatonReasearch |
| NEATGenome | ----------------------------------------------------------------------------- http://www. | Class | org.encog.neural.neat.training | HeatonReasearch |
| NEATGenomeFactory | This interface defines additional methods defined to create NEAT genomes. | Interface | org.encog.neural.neat | HeatonReasearch |
| NEATInnovation | previously tried with a neural network. | Class | org.encog.neural.neat.training | HeatonReasearch |
| NEATInnovationList | NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks. | Class | org.encog.neural.neat.training | HeatonReasearch |
| NEATInnovationType | enum NEATInnovationTypeThe type of NEAT innovation. | Class | org.encog.neural.neat.training | HeatonReasearch |
| NEATLink | NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks. | Class | org.encog.neural.neat | HeatonReasearch |
| NEATLinkGene | NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks. | Class | org.encog.neural.neat.training | HeatonReasearch |
| NEATMutateAddLink | Mutates a NEAT genome by adding a link. | Class | org.encog.neural.neat.training.opp | HeatonReasearch |
| NEATMutateAddNode | Mutate a genome by adding a new node. | Class | org.encog.neural.neat.training.opp | HeatonReasearch |
| NEATMutateRemoveLink | Mutate a genome by removing a random link. | Class | org.encog.neural.neat.training.opp | HeatonReasearch |
| NEATMutateWeights | Mutate the weights of a genome. | Class | org.encog.neural.neat.training.opp | HeatonReasearch |
| NEATMutation | This class represents a NEAT mutation. | Class | org.encog.neural.neat.training.opp | HeatonReasearch |
| NEATNetwork | NEAT networks relieve the programmer of the need to define the hidden layer structure of the neural network. | Class | org.encog.neural.neat | HeatonReasearch |
| NEATNeuronGene | NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks. | Class | org.encog.neural.neat.training | HeatonReasearch |
| NEATNeuronType | The types of neurons supported by NEAT. | Class | org.encog.neural.neat | HeatonReasearch |
| NEATPopulation | A population for a NEAT or HyperNEAT system. | Class | org.encog.neural.neat | HeatonReasearch |
| NEATUtil | NEAT does not make use of a special trainer. | Class | org.encog.neural.neat | HeatonReasearch |
| NeighborhoodBubble | A neighborhood function that uses a simple bubble. | Class | org.encog.neural.som.training.basic.neighborhood | HeatonReasearch |
| NeighborhoodFunction | Defines how a neighborhood function should work in competitive training. | Interface | org.encog.neural.som.training.basic.neighborhood | HeatonReasearch |
| NeighborhoodRBF | Class | org.encog.neural.som.training.basic.neighborhood | HeatonReasearch | |
| NeighborhoodRBF1D | A neighborhood function based on an RBF function. | Class | org.encog.neural.som.training.basic.neighborhood | HeatonReasearch |
| NeighborhoodSingle | A very simple neighborhood function that will return 1. | Class | org.encog.neural.som.training.basic.neighborhood | HeatonReasearch |
| NelderMeadTraining | The Nelder-Mead method is a commonly used parameter optimization method that can be used for neural network training. | Class | org.encog.neural.networks.training.nm | HeatonReasearch |
| NetworkCODEC | This class will extract the "long term memory" of a neural network, that is the weights and bias values into an array. | Class | org.encog.neural.networks.structure | HeatonReasearch |
| NetworkFold | The network for one fold of a cross validation. | Class | org.encog.neural.networks.training.cross | HeatonReasearch |
| NetworkPattern | Specify which network pattern to use. | Class | org.encog.neural.prune | HeatonReasearch |
| NeuralData | This is an alias class for Encog 2. | Interface | org.encog.neural.data | HeatonReasearch |
| NeuralDataMapping | Used to map one neural data object to another. | Class | org.encog.neural.networks | HeatonReasearch |
| NeuralDataPair | This is an alias class for Encog 2. | Interface | org.encog.neural.data | HeatonReasearch |
| NeuralDataSet | This is an alias class for Encog 2. | Interface | org.encog.neural.data | HeatonReasearch |
| NeuralNetworkError | Used by the neural network classes to indicate an error. | Class | org.encog.neural | HeatonReasearch |
| NeuralNetworkPattern | Patterns are used to create common sorts of neural networks. | Interface | org.encog.neural.pattern | HeatonReasearch |
| NeuralPSO | Iteratively trains a population of neural networks by applying particle swarm optimisation (PSO). | Class | org.encog.neural.networks.training.pso | HeatonReasearch |
| NeuralPSOWorker | PSO multi-treaded worker. | Class | org.encog.neural.networks.training.pso | HeatonReasearch |
| NeuralSimulatedAnnealing | This class implements a simulated annealing training algorithm for neural networks. | Class | org.encog.neural.networks.training.anneal | HeatonReasearch |
| NeuralSimulatedAnnealingHelper | Simple class used by the neural simulated annealing. | Class | org.encog.neural.networks.training.anneal | HeatonReasearch |
| NeuralStructure | Holds "cached" information about the structure of the neural network. | Class | org.encog.neural.networks.structure | HeatonReasearch |
| NeuronTask | Defines a task that is carried out for every neuron. | Interface | org.encog.neural.freeform.task | HeatonReasearch |
| OriginalNEATSpeciation | The original NEAT Speciation Strategy. | Class | org.encog.neural.neat.training.species | HeatonReasearch |
| OutputErrorFunction | Class | org.encog.neural.error | HeatonReasearch | |
| PatternError | This class is thrown when an error occurs while using one of the neural network pattern classes. | Class | org.encog.neural.pattern | HeatonReasearch |
| PerformerTask | A task to be performed. | Class | org.encog.neural.networks.training.concurrent.performers | HeatonReasearch |
| PersistART1 | Persist an ART1 network. | Class | org.encog.neural.art | HeatonReasearch |
| PersistBAM | Persist the BAM network. | Class | org.encog.neural.bam | HeatonReasearch |
| PersistBasicNetwork | Persist a basic network. | Class | org.encog.neural.networks | HeatonReasearch |
| PersistBasicPNN | Class | org.encog.neural.pnn | HeatonReasearch | |
| PersistBoltzmann | Persist the Boltzmann machine. | Class | org.encog.neural.thermal | HeatonReasearch |
| PersistCPN | Persist a CPN network. | Class | org.encog.neural.cpn | HeatonReasearch |
| PersistHopfield | Persist the Hopfield network. | Class | org.encog.neural.thermal | HeatonReasearch |
| PersistNEATPopulation | Persist a NEAT or HyperNEAT network. | Class | org.encog.neural.neat | HeatonReasearch |
| PersistRBFNetwork | Persist a RBF network. | Class | org.encog.neural.rbf | HeatonReasearch |
| PersistSOM | Class | org.encog.neural.som | HeatonReasearch | |
| PersistTrainingContinuation | Persist the training continuation. | Class | org.encog.neural.networks.training.propagation | HeatonReasearch |
| PNNKernelType | Specifies the kernel type for the PNN. | Class | org.encog.neural.pnn | HeatonReasearch |
| PNNOutputMode | The output mode that will be used by the PNN. | Class | org.encog.neural.pnn | HeatonReasearch |
| PNNPattern | Pattern to create a PNN. | Class | org.encog.neural.pattern | HeatonReasearch |
| Propagation | methods. | Class | org.encog.neural.networks.training.propagation | HeatonReasearch |
| PruneIncremental | This class is used to help determine the optimal configuration for the hidden layers of a neural network. | Class | org.encog.neural.prune | HeatonReasearch |
| PruneSelective | Prune a neural network selectively. | Class | org.encog.neural.prune | HeatonReasearch |
| QuickPropagation | QPROP is an efficient training method that is based on Newton's Method. | Class | org.encog.neural.networks.training.propagation.quick | HeatonReasearch |
| RadialBasisPattern | A radial basis function (RBF) network uses several radial basis functions to provide a more dynamic hidden layer activation function than many other types | Class | org.encog.neural.pattern | HeatonReasearch |
| RBFNetwork | Class | org.encog.neural.rbf | HeatonReasearch | |
| RegularizationStrategy | Class | org.encog.neural.networks.training.strategy | HeatonReasearch | |
| ResilientPropagation | One problem with the backpropagation algorithm is that the magnitude of the partial derivative is usually too large or too small. | Class | org.encog.neural.networks.training.propagation.resilient | HeatonReasearch |
| RPROPConst | Constants used for Resilient Propagation (RPROP) training. | Class | org.encog.neural.networks.training.propagation.resilient | HeatonReasearch |
| RPROPJob | A training definition for RPROP training. | Class | org.encog.neural.networks.training.concurrent.jobs | HeatonReasearch |
| RPROPType | Allows the type of RPROP to be defined. | Class | org.encog.neural.networks.training.propagation.resilient | HeatonReasearch |
| ScaledConjugateGradient | This is a training class that makes use of scaled conjugate gradient methods. | Class | org.encog.neural.networks.training.propagation.scg | HeatonReasearch |
| SelectFixed | Select a fixed number of link genes. | Class | org.encog.neural.neat.training.opp.links | HeatonReasearch |
| SelectLinks | This interface defines ways that NEAT links can be chosen for mutation. | Interface | org.encog.neural.neat.training.opp.links | HeatonReasearch |
| SelectProportion | Select a random proportion of links to mutate. | Class | org.encog.neural.neat.training.opp.links | HeatonReasearch |
| SmartLearningRate | Attempt to automatically set the learning rate in a learning method that supports a learning rate. | Class | org.encog.neural.networks.training.strategy | HeatonReasearch |
| SmartMomentum | Class | org.encog.neural.networks.training.strategy | HeatonReasearch | |
| SOM | A self organizing map neural network. | Class | org.encog.neural.som | HeatonReasearch |
| SOMClusterCopyTraining | SOM cluster copy is a very simple trainer for SOM's. | Class | org.encog.neural.som.training.clustercopy | HeatonReasearch |
| SOMPattern | A self organizing map is a neural network pattern with an input and output layer. | Class | org.encog.neural.pattern | HeatonReasearch |
| Substrate | The substrate defines the structure of the produced HyperNEAT network. | Class | org.encog.neural.hyperneat.substrate | HeatonReasearch |
| SubstrateFactory | Produce substrates for various topologies. | Class | org.encog.neural.hyperneat.substrate | HeatonReasearch |
| SubstrateLink | ----------------------------------------------------------------------------- http://www. | Class | org.encog.neural.hyperneat.substrate | HeatonReasearch |
| SubstrateNode | A substrate node. | Class | org.encog.neural.hyperneat.substrate | HeatonReasearch |
| SVD | Perform a SVD decomp on a matrix. | Class | org.encog.neural.rbf.training | HeatonReasearch |
| SVDTraining | Train a RBF neural network using a SVD. | Class | org.encog.neural.rbf.training | HeatonReasearch |
| SVMPattern | A pattern to create support vector machines. | Class | org.encog.neural.pattern | HeatonReasearch |
| TempTrainingData | Interface | org.encog.neural.freeform | HeatonReasearch | |
| ThermalNetwork | The thermal network forms the base class for Hopfield and Boltzmann machines. | Class | org.encog.neural.thermal | HeatonReasearch |
| Train | This is an alias class for Encog 2. | Interface | org.encog.neural.networks.training | HeatonReasearch |
| TrainAdaline | Train an ADALINE neural network. | Class | org.encog.neural.networks.training.simple | HeatonReasearch |
| TrainBasicPNN | Class | org.encog.neural.networks.training.pnn | HeatonReasearch | |
| TrainingContinuation | Allows training to be continued. | Class | org.encog.neural.networks.training.propagation | HeatonReasearch |
| TrainingError | Thrown when a training error occurs. | Class | org.encog.neural.networks.training | HeatonReasearch |
| TrainingJob | Base class for all concurrent training jobs. | Class | org.encog.neural.networks.training.concurrent.jobs | HeatonReasearch |
| TrainingSetScore | Calculate a score based on a training set. | Class | org.encog.neural.networks.training | HeatonReasearch |
| TrainInstar | Used for Instar training of a CPN neural network. | Class | org.encog.neural.cpn.training | HeatonReasearch |
| TrainOutstar | Used for Instar training of a CPN neural network. | Class | org.encog.neural.cpn.training | HeatonReasearch |