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Uses of BasicNetwork in org.encog.mathutil.matrices.hessian |
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Fields in org.encog.mathutil.matrices.hessian declared as BasicNetwork | |
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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 | |
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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 |
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Methods in org.encog.mathutil.randomize with parameters of type BasicNetwork | |
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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 |
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Constructors in org.encog.neural.freeform with parameters of type BasicNetwork | |
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FreeformNetwork(BasicNetwork network)
Craete a freeform network from a basic network. |
Uses of BasicNetwork in org.encog.neural.networks |
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Methods in org.encog.neural.networks with parameters of type BasicNetwork | |
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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 |
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Methods in org.encog.neural.networks.layers that return BasicNetwork | |
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BasicNetwork |
Layer.getNetwork()
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BasicNetwork |
BasicLayer.getNetwork()
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Methods in org.encog.neural.networks.layers with parameters of type BasicNetwork | |
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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 |
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Methods in org.encog.neural.networks.structure that return BasicNetwork | |
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BasicNetwork |
NeuralStructure.getNetwork()
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Methods in org.encog.neural.networks.structure with parameters of type BasicNetwork | |
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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 | |
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AnalyzeNetwork(BasicNetwork network)
Construct a network analyze class. |
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NeuralStructure(BasicNetwork network)
Construct a structure object for the specified network. |
Uses of BasicNetwork in org.encog.neural.networks.training.concurrent.jobs |
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Methods in org.encog.neural.networks.training.concurrent.jobs that return BasicNetwork | |
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BasicNetwork |
TrainingJob.getNetwork()
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Methods in org.encog.neural.networks.training.concurrent.jobs with parameters of type BasicNetwork | |
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void |
TrainingJob.setNetwork(BasicNetwork network)
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Constructors in org.encog.neural.networks.training.concurrent.jobs with parameters of type BasicNetwork | |
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BPROPJob(BasicNetwork network,
MLDataSet training,
boolean loadToMemory,
double learningRate,
double momentum)
Construct a job definition for RPROP. |
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RPROPJob(BasicNetwork network,
MLDataSet training,
boolean loadToMemory)
Construct an RPROP job. |
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TrainingJob(BasicNetwork network,
MLDataSet training,
boolean loadToMemory)
Construct a training job. |
Uses of BasicNetwork in org.encog.neural.networks.training.lma |
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Constructors in org.encog.neural.networks.training.lma with parameters of type BasicNetwork | |
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LevenbergMarquardtTraining(BasicNetwork network,
MLDataSet training)
Construct the LMA object. |
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LevenbergMarquardtTraining(BasicNetwork network,
MLDataSet training,
ComputeHessian h)
Construct the LMA object. |
Uses of BasicNetwork in org.encog.neural.networks.training.nm |
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Constructors in org.encog.neural.networks.training.nm with parameters of type BasicNetwork | |
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NelderMeadTraining(BasicNetwork network,
MLDataSet training)
Construct a Nelder Mead trainer with a step size of 100. |
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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 |
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Fields in org.encog.neural.networks.training.pso declared as BasicNetwork | |
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protected BasicNetwork[] |
NeuralPSO.m_networks
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Methods in org.encog.neural.networks.training.pso with parameters of type BasicNetwork | |
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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 | |
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NeuralPSO(BasicNetwork network,
MLDataSet trainingSet)
Construct a PSO using a training set score function, 20 particles and the NguyenWidrowRandomizer randomizer. |
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NeuralPSO(BasicNetwork network,
Randomizer randomizer,
CalculateScore calculateScore,
int populationSize)
Constructor. |
Uses of BasicNetwork in org.encog.neural.networks.training.simple |
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Constructors in org.encog.neural.networks.training.simple with parameters of type BasicNetwork | |
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TrainAdaline(BasicNetwork network,
MLDataSet training,
double learningRate)
Construct an ADALINE trainer. |
Uses of BasicNetwork in org.encog.neural.prune |
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Methods in org.encog.neural.prune that return BasicNetwork | |
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BasicNetwork |
PruneIncremental.getBestNetwork()
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BasicNetwork |
PruneSelective.getNetwork()
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BasicNetwork[] |
PruneIncremental.getTopNetworks()
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Methods in org.encog.neural.prune with parameters of type BasicNetwork | |
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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 | |
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PruneSelective(BasicNetwork network)
Construct an object prune the neural network. |
Uses of BasicNetwork in org.encog.platformspecific.j2se |
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Methods in org.encog.platformspecific.j2se with parameters of type BasicNetwork | |
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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 |
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Methods in org.encog.util.benchmark with parameters of type BasicNetwork | |
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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 |
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Methods in org.encog.util.simple that return BasicNetwork | |
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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 | |
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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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