Modifier and Type | Field and Description |
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protected BasicNetwork |
BasicHessian.network
The neural network that we would like to train.
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Modifier and Type | Method and Description |
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void |
HessianFD.init(BasicNetwork theNetwork,
MLDataSet theTraining)
Init the class.
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void |
HessianCR.init(BasicNetwork theNetwork,
MLDataSet theTraining)
Init the class.
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void |
ComputeHessian.init(BasicNetwork theNetwork,
MLDataSet theTraining)
Init the class.
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void |
BasicHessian.init(BasicNetwork theNetwork,
MLDataSet theTraining)
Init the class.
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Modifier and Type | Method and Description |
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void |
ConsistentRandomizer.randomize(BasicNetwork network)
Randomize the network.
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void |
BasicRandomizer.randomize(BasicNetwork network,
int fromLayer)
Randomize one level of a neural network.
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void |
FanInRandomizer.randomize(BasicNetwork network,
int fromLayer)
Randomize one level of a neural network.
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Constructor and Description |
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FreeformNetwork(BasicNetwork network)
Craete a freeform network from a basic network.
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Modifier and Type | Method and Description |
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boolean |
BasicNetwork.equals(BasicNetwork other,
int precision)
Determine if this neural network is equal to another.
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Modifier and Type | Method and Description |
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BasicNetwork |
Layer.getNetwork() |
BasicNetwork |
BasicLayer.getNetwork() |
Modifier and Type | Method and Description |
---|---|
void |
Layer.setNetwork(BasicNetwork network)
Set the network that this layer belongs to.
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void |
BasicLayer.setNetwork(BasicNetwork network)
Set the network for this layer.
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Modifier and Type | Method and Description |
---|---|
BasicNetwork |
NeuralStructure.getNetwork() |
Modifier and Type | Method and Description |
---|---|
static boolean |
NetworkCODEC.equals(BasicNetwork network1,
BasicNetwork network2)
Determine if the two neural networks are equal.
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static boolean |
NetworkCODEC.equals(BasicNetwork network1,
BasicNetwork network2,
int precision)
Determine if the two neural networks are equal.
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Constructor and Description |
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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.
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Modifier and Type | Method and Description |
---|---|
BasicNetwork |
TrainingJob.getNetwork() |
Modifier and Type | Method and Description |
---|---|
void |
TrainingJob.setNetwork(BasicNetwork network) |
Constructor and Description |
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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.
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Constructor and Description |
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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.
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Constructor and Description |
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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.
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Modifier and Type | Field and Description |
---|---|
protected BasicNetwork[] |
NeuralPSO.m_networks |
Modifier and Type | Method and Description |
---|---|
void |
NeuralPSO.setInitialPopulation(BasicNetwork[] initialPopulation)
Keep a reference to the passed population of networks.
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Constructor and Description |
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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.
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Constructor and Description |
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TrainAdaline(BasicNetwork network,
MLDataSet training,
double learningRate)
Construct an ADALINE trainer.
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Modifier and Type | Method and Description |
---|---|
BasicNetwork |
PruneIncremental.getBestNetwork() |
BasicNetwork |
PruneSelective.getNetwork() |
BasicNetwork[] |
PruneIncremental.getTopNetworks() |
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.
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Constructor and Description |
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PruneSelective(BasicNetwork network)
Construct an object prune the neural network.
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Modifier and Type | Method and Description |
---|---|
static void |
TrainingDialog.trainDialog(BasicNetwork network,
MLDataSet trainingSet)
Train using SCG and display progress to a dialog box.
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static void |
TrainingDialog.trainDialog(MLTrain train,
BasicNetwork network,
MLDataSet trainingSet)
Train, using the specified training method, display progress to a dialog
box.
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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.
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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.
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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.
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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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