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

- Packages that use BasicNetwork
  Package | Description
  --- | ---
  org.encog.mathutil.matrices.hessian |
  org.encog.mathutil.randomize |
  org.encog.neural.freeform |
  org.encog.neural.networks |
  org.encog.neural.networks.layers |
  org.encog.neural.networks.structure |
  org.encog.neural.networks.training.concurrent.jobs |
  org.encog.neural.networks.training.lma |
  org.encog.neural.networks.training.nm |
  org.encog.neural.networks.training.pso |
  org.encog.neural.networks.training.simple |
  org.encog.neural.prune |
  org.encog.platformspecific.j2se |
  org.encog.util.benchmark |
  org.encog.util.simple |

- - ### Uses of BasicNetwork in org.encog.mathutil.matrices.hessian

    Fields in org.encog.mathutil.matrices.hessian declared as BasicNetwork
    Modifier and Type | Field and Description
    --- | ---
    `protected BasicNetwork` | BasicHessian.`network` The neural network that we would like to train.

    Methods in org.encog.mathutil.matrices.hessian with parameters of type BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `void` | HessianFD.`init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.
    `void` | HessianCR.`init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.
    `void` | ComputeHessian.`init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.
    `void` | BasicHessian.`init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.

  - ### Uses of BasicNetwork in org.encog.mathutil.randomize

    Methods in org.encog.mathutil.randomize with parameters of type BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `void` | ConsistentRandomizer.`randomize(BasicNetwork network)` Randomize the network.
    `void` | BasicRandomizer.`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.

  - ### Uses of BasicNetwork in org.encog.neural.freeform

    Constructors in org.encog.neural.freeform with parameters of type BasicNetwork
    Constructor and Description
    `FreeformNetwork(BasicNetwork network)` Craete a freeform network from a basic network.

  - ### Uses of BasicNetwork in org.encog.neural.networks

    Methods in org.encog.neural.networks with parameters of type BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `BasicNetwork` | Layer.`getNetwork()`
    `BasicNetwork` | BasicLayer.`getNetwork()`

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

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

    Methods in org.encog.neural.networks.structure that return BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `BasicNetwork` | NeuralStructure.`getNetwork()`

    Methods in org.encog.neural.networks.structure with parameters of type BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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.concurrent.jobs

    Methods in org.encog.neural.networks.training.concurrent.jobs that return BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `BasicNetwork` | TrainingJob.`getNetwork()`

    Methods in org.encog.neural.networks.training.concurrent.jobs with parameters of type BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `void` | TrainingJob.`setNetwork(BasicNetwork network)`

    Constructors in org.encog.neural.networks.training.concurrent.jobs with parameters of type BasicNetwork
    Constructor and Description
    `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.lma

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

  - ### Uses of BasicNetwork in org.encog.neural.networks.training.nm

    Constructors in org.encog.neural.networks.training.nm with parameters of type BasicNetwork
    Constructor and Description
    `NelderMeadTraining(BasicNetwork network, MLDataSet training)` Construct a Nelder Mead trainer with a step size of 100.
    `NelderMeadTraining(BasicNetwork network, MLDataSet training, double stepValue)` Construct a Nelder Mead trainer with a definable step.

  - ### Uses of BasicNetwork in org.encog.neural.networks.training.pso

    Fields in org.encog.neural.networks.training.pso declared as BasicNetwork
    Modifier and Type | Field and Description
    --- | ---
    `protected BasicNetwork[]` | NeuralPSO.`m_networks`

    Methods in org.encog.neural.networks.training.pso with parameters of type BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `void` | NeuralPSO.`setInitialPopulation(BasicNetwork[] initialPopulation)` Keep a reference to the passed population of networks.

    Constructors in org.encog.neural.networks.training.pso with parameters of type BasicNetwork
    Constructor and Description
    `NeuralPSO(BasicNetwork network, MLDataSet trainingSet)` Construct a PSO using a training set score function, 20 particles and the NguyenWidrowRandomizer randomizer.
    `NeuralPSO(BasicNetwork network, Randomizer randomizer, CalculateScore calculateScore, int populationSize)` Constructor.

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

    Constructors in org.encog.neural.networks.training.simple with parameters of type BasicNetwork
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `BasicNetwork` | PruneIncremental.`getBestNetwork()`
    `BasicNetwork` | PruneSelective.`getNetwork()`
    `BasicNetwork[]` | PruneIncremental.`getTopNetworks()`

    Methods in org.encog.neural.prune with parameters of type BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `PruneSelective(BasicNetwork network)` Construct an object prune the neural network.

  - ### Uses of BasicNetwork in org.encog.platformspecific.j2se

    Methods in org.encog.platformspecific.j2se with parameters of type BasicNetwork
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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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