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#Org.encog.neural.networks Classes and Interfaces - 50 results found.
| Name | Description | Type | Package | Framework |
| AnalyzeNetwork | Allows the weights and bias values of the neural network to be analyzed. | Class | org.encog.neural.networks.structure | HeatonReasearch |
| Backpropagation | This class implements a backpropagation training algorithm for feed forward neural networks. | Class | org.encog.neural.networks.training.propagation.back | 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 |
| BatchSize | The batch size. | Interface | org.encog.neural.networks.training | 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 |
| ContainsFlat | Interface | org.encog.neural.networks | 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| NeuralDataMapping | Used to map one neural data object to another. | Class | org.encog.neural.networks | 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 |
| PerformerTask | A task to be performed. | Class | org.encog.neural.networks.training.concurrent.performers | HeatonReasearch |
| PersistBasicNetwork | Persist a basic network. | Class | org.encog.neural.networks | HeatonReasearch |
| PersistTrainingContinuation | Persist the training continuation. | Class | org.encog.neural.networks.training.propagation | HeatonReasearch |
| Propagation | methods. | Class | org.encog.neural.networks.training.propagation | HeatonReasearch |
| QuickPropagation | QPROP is an efficient training method that is based on Newton's Method. | Class | org.encog.neural.networks.training.propagation.quick | 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 |
| 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 | |
| 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 |