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## Uses of Class
org.encog.neural.networks.BasicNetwork

Packages that use BasicNetwork
org.encog.mathutil.randomize |
org.encog.neural.networks | This package contains the neural network machine learning methods.
org.encog.neural.networks.layers |
org.encog.neural.networks.structure | This package contains classes used to handle the structure of a neural network.
org.encog.neural.networks.training.anneal | This package trains neural network using simulated annealing.
org.encog.neural.networks.training.concurrent.jobs | This package provides the performers to perform concurrent training jobs.
org.encog.neural.networks.training.genetic | This package provides genetic training for neural networks.
org.encog.neural.networks.training.lma | This package provides Levenberg Marquardt training for neural networks.
org.encog.neural.networks.training.simple | This package provides simple ADALINE training.
org.encog.neural.prune | This package contains the classes to prune a neural network.
org.encog.neural.som.training.basic | This package implements neighborhood training for the SOM.
org.encog.platformspecific.j2se |
org.encog.util.benchmark |
org.encog.util.simple |

Uses of BasicNetwork in org.encog.mathutil.randomize

Methods in org.encog.mathutil.randomize with parameters of type BasicNetwork
`void` | `ConsistentRandomizer.randomize(BasicNetwork network)` Randomize the network.
`void` | `NguyenWidrowRandomizer.randomize(BasicNetwork network, int fromLayer)` Randomize one level of a neural network.
`void` | `FanInRandomizer.randomize(BasicNetwork network, int fromLayer)` Randomize one level of a neural network.
`void` | `BasicRandomizer.randomize(BasicNetwork network, int fromLayer)` Randomize one level of a neural network.

Uses of BasicNetwork in org.encog.neural.networks

Methods in org.encog.neural.networks with parameters of type BasicNetwork
`boolean` | `BasicNetwork.equals(BasicNetwork other)` Compare the two neural networks.
`boolean` | `BasicNetwork.equals(BasicNetwork other, int precision)` Determine if this neural network is equal to another.

Uses of BasicNetwork in org.encog.neural.networks.layers

Methods in org.encog.neural.networks.layers that return BasicNetwork
`BasicNetwork` | `BasicLayer.getNetwork()`
`BasicNetwork` | `Layer.getNetwork()`

Methods in org.encog.neural.networks.layers with parameters of type BasicNetwork
`void` | `BasicLayer.setNetwork(BasicNetwork network)` Set the network for this layer.
`void` | `Layer.setNetwork(BasicNetwork network)` Set the network that this layer belongs to.

Uses of BasicNetwork in org.encog.neural.networks.structure

Methods in org.encog.neural.networks.structure that return BasicNetwork
`BasicNetwork` | `NeuralStructure.getNetwork()`

Methods in org.encog.neural.networks.structure with parameters of type BasicNetwork
`static boolean` | `NetworkCODEC.equals(BasicNetwork network1, BasicNetwork network2)` Determine if the two neural networks are equal.
`static boolean` | `NetworkCODEC.equals(BasicNetwork network1, BasicNetwork network2, int precision)` Determine if the two neural networks are equal.

Constructors in org.encog.neural.networks.structure with parameters of type BasicNetwork
`AnalyzeNetwork(BasicNetwork network)` Construct a network analyze class.
`NeuralStructure(BasicNetwork network)` Construct a structure object for the specified network.

Uses of BasicNetwork in org.encog.neural.networks.training.anneal

Methods in org.encog.neural.networks.training.anneal that return BasicNetwork
`BasicNetwork` | `NeuralSimulatedAnnealing.getMethod()` Get the current best machine learning method from the training.

Constructors in org.encog.neural.networks.training.anneal with parameters of type BasicNetwork
`NeuralSimulatedAnnealing(BasicNetwork network, CalculateScore calculateScore, double startTemp, double stopTemp, int cycles)` Construct a simulated annleaing trainer for a feedforward neural network.

Uses of BasicNetwork in org.encog.neural.networks.training.concurrent.jobs

Methods in org.encog.neural.networks.training.concurrent.jobs that return BasicNetwork
`BasicNetwork` | `TrainingJob.getNetwork()`

Methods in org.encog.neural.networks.training.concurrent.jobs with parameters of type BasicNetwork
`void` | `TrainingJob.setNetwork(BasicNetwork network)`

Constructors in org.encog.neural.networks.training.concurrent.jobs with parameters of type BasicNetwork
`BPROPJob(BasicNetwork network, MLDataSet training, boolean loadToMemory, double learningRate, double momentum)` Construct a job definition for RPROP.
`RPROPJob(BasicNetwork network, MLDataSet training, boolean loadToMemory)` Construct an RPROP job.
`TrainingJob(BasicNetwork network, MLDataSet training, boolean loadToMemory)` Construct a training job.

Uses of BasicNetwork in org.encog.neural.networks.training.genetic

Constructors in org.encog.neural.networks.training.genetic with parameters of type BasicNetwork
`NeuralGeneticAlgorithm(BasicNetwork network, Randomizer randomizer, CalculateScore calculateScore, int populationSize, double mutationPercent, double percentToMate)` Construct a neural genetic algorithm.
`NeuralGenome(BasicNetwork network)` Construct a neural genome.

Uses of BasicNetwork in org.encog.neural.networks.training.lma

Constructors in org.encog.neural.networks.training.lma with parameters of type BasicNetwork
`LevenbergMarquardtTraining(BasicNetwork network, MLDataSet training)` Construct the LMA object.

Uses of BasicNetwork in org.encog.neural.networks.training.simple

Constructors in org.encog.neural.networks.training.simple with parameters of type BasicNetwork
`TrainAdaline(BasicNetwork network, MLDataSet training, double learningRate)` Construct an ADALINE trainer.

Uses of BasicNetwork in org.encog.neural.prune

Methods in org.encog.neural.prune that return BasicNetwork
`BasicNetwork` | `PruneIncremental.getBestNetwork()`
`BasicNetwork` | `PruneSelective.getNetwork()`
`BasicNetwork[]` | `PruneIncremental.getTopNetworks()`

Methods in org.encog.neural.prune with parameters of type BasicNetwork
`static String` | `PruneIncremental.networkToString(BasicNetwork network)` Format the network as a human readable string that lists the hidden layers.

Constructors in org.encog.neural.prune with parameters of type BasicNetwork
`PruneSelective(BasicNetwork network)` Construct an object prune the neural network.

Uses of BasicNetwork in org.encog.neural.som.training.basic

Methods in org.encog.neural.som.training.basic that return BasicNetwork
`BasicNetwork` | `BasicTrainSOM.getMethod()` Get the current best machine learning method from the training.

Uses of BasicNetwork in org.encog.platformspecific.j2se

Methods in org.encog.platformspecific.j2se with parameters of type BasicNetwork
`static void` | `TrainingDialog.trainDialog(BasicNetwork network, MLDataSet trainingSet)` Train using SCG and display progress to a dialog box.
`static void` | `TrainingDialog.trainDialog(MLTrain train, BasicNetwork network, MLDataSet trainingSet)` Train, using the specified training method, display progress to a dialog box.

Uses of BasicNetwork in org.encog.util.benchmark

Methods in org.encog.util.benchmark with parameters of type BasicNetwork
`static int` | `Evaluate.evaluateTrain(BasicNetwork network, MLDataSet training)` Evaluate how long it takes to calculate the error for the network.

Uses of BasicNetwork in org.encog.util.simple

Methods in org.encog.util.simple that return BasicNetwork
`static BasicNetwork` | `EncogUtility.simpleFeedForward(int input, int hidden1, int hidden2, int output, boolean tanh)` Create a simple feedforward neural network.

Methods in org.encog.util.simple with parameters of type BasicNetwork
`static void` | `EncogUtility.trainConsole(BasicNetwork network, MLDataSet trainingSet, int minutes)` Train the neural network, using SCG training, and output status to the console.
`static void` | `EncogUtility.trainConsole(MLTrain train, BasicNetwork network, MLDataSet trainingSet, int minutes)` Train the network, using the specified training algorithm, and send the output to the console.

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