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| Uses of BasicNetwork in org.encog.mathutil.randomize |
|---|
| Methods in org.encog.mathutil.randomize with parameters of type BasicNetwork | |
|---|---|
void |
Randomizer.randomize(BasicNetwork network)
Randomize the synapses and bias values in the basic network based on an array, modify the array. |
void |
NguyenWidrowRandomizer.randomize(BasicNetwork network)
The Nguyen-Widrow initialization algorithm is the following : 1. |
void |
ConsistentRandomizer.randomize(BasicNetwork network)
Randomize the network. |
void |
BasicRandomizer.randomize(BasicNetwork network)
Randomize the synapses and biases in the basic network based on an array, modify the array. |
void |
FanInRandomizer.randomize(BasicNetwork network,
Synapse synapse)
Randomize a synapse, only randomize those connections that are actually connected. |
void |
BasicRandomizer.randomize(BasicNetwork network,
Synapse synapse)
Randomize a synapse, only randomize those connections that are actually connected. |
| Uses of BasicNetwork in org.encog.neural.networks |
|---|
| Methods in org.encog.neural.networks with parameters of type BasicNetwork | |
|---|---|
boolean |
Network.equals(BasicNetwork other)
Compare the two neural networks. |
boolean |
BasicNetwork.equals(BasicNetwork other)
Compare the two neural networks. |
boolean |
Network.equals(BasicNetwork other,
int precision)
Determine if this neural network is equal to another. |
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 |
Layer.getNetwork()
|
BasicNetwork |
BasicLayer.getNetwork()
|
| Methods in org.encog.neural.networks.layers with parameters of type BasicNetwork | |
|---|---|
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.logic |
|---|
| Methods in org.encog.neural.networks.logic that return BasicNetwork | |
|---|---|
BasicNetwork |
FeedforwardLogic.getNetwork()
|
BasicNetwork |
BAMLogic.getNetwork()
|
BasicNetwork |
ARTLogic.getNetwork()
|
| Methods in org.encog.neural.networks.logic with parameters of type BasicNetwork | |
|---|---|
void |
ThermalLogic.init(BasicNetwork network)
Setup the network logic, read parameters from the network. |
void |
NeuralLogic.init(BasicNetwork network)
Setup the network logic, read parameters from the network. |
void |
FeedforwardLogic.init(BasicNetwork network)
Setup the network logic, read parameters from the network. |
void |
BoltzmannLogic.init(BasicNetwork network)
Setup the network logic, read parameters from the network. |
void |
BAMLogic.init(BasicNetwork network)
Setup the network logic, read parameters from the network. |
void |
ARTLogic.init(BasicNetwork network)
Setup the network logic, read parameters from the network. |
void |
ART1Logic.init(BasicNetwork network)
Setup the network logic, read parameters from the network. |
| 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 void |
NetworkCODEC.arrayToNetwork(double[] array,
BasicNetwork network)
Use an array to populate the memory of the neural network. |
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. |
static int |
NetworkCODEC.networkSize(BasicNetwork network)
|
static double[] |
NetworkCODEC.networkToArray(BasicNetwork network)
Convert to an array. |
| Constructors in org.encog.neural.networks.structure with parameters of type BasicNetwork | |
|---|---|
AnalyzeNetwork(BasicNetwork network)
Construct a network analyze class. |
|
CalculateDepth(BasicNetwork network)
Construct the depth calculation object. |
|
NeuralStructure(BasicNetwork network)
Construct a structure object for the specified network. |
|
| Uses of BasicNetwork in org.encog.neural.networks.svm |
|---|
| Subclasses of BasicNetwork in org.encog.neural.networks.svm | |
|---|---|
class |
SVMNetwork
This is a network that is backed by one or more Support Vector Machines (SVM). |
| Uses of BasicNetwork in org.encog.neural.networks.training |
|---|
| Methods in org.encog.neural.networks.training that return BasicNetwork | |
|---|---|
BasicNetwork |
Train.getNetwork()
Get the current best network from the training. |
| Methods in org.encog.neural.networks.training with parameters of type BasicNetwork | |
|---|---|
double |
TrainingSetScore.calculateScore(BasicNetwork network)
Calculate the score for the network. |
double |
CalculateScore.calculateScore(BasicNetwork network)
Calculate this network's score. |
| Uses of BasicNetwork in org.encog.neural.networks.training.anneal |
|---|
| Methods in org.encog.neural.networks.training.anneal that return BasicNetwork | |
|---|---|
BasicNetwork |
NeuralSimulatedAnnealing.getNetwork()
Get the best network 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.competitive |
|---|
| Methods in org.encog.neural.networks.training.competitive that return BasicNetwork | |
|---|---|
BasicNetwork |
CompetitiveTraining.getNetwork()
|
| Constructors in org.encog.neural.networks.training.competitive with parameters of type BasicNetwork | |
|---|---|
CompetitiveTraining(BasicNetwork network,
double learningRate,
NeuralDataSet training,
NeighborhoodFunction neighborhood)
Create an instance of competitive training. |
|
| 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,
NeuralDataSet training,
boolean loadToMemory,
double learningRate,
double momentum)
Construct a job definition for RPROP. |
|
BPROPJob(BasicNetwork network,
NeuralDataSet training,
boolean loadToMemory,
double learningRate,
double momentum,
double localRatio,
int globalRatio,
double segmentationRatio,
int iterationsPer)
Construct a job definition for RPROP. |
|
RPROPJob(BasicNetwork network,
NeuralDataSet training,
boolean loadToMemory)
Construct an RPROP job. |
|
RPROPJob(BasicNetwork network,
NeuralDataSet training,
boolean loadToMemory,
double initialUpdate,
double maxStep,
double localRatio,
int globalRatio,
double segmentationRatio,
int iterationsPer)
Construct an RPROP job. |
|
RPROPJob(BasicNetwork network,
NeuralDataSet training,
boolean loadToMemory,
double localRatio,
int globalRatio,
double segmentationRatio,
int iterationsPer)
Construct an RPROP job. |
|
TrainingJob(BasicNetwork network,
NeuralDataSet training,
boolean loadToMemory)
Construct a training job. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.cpn |
|---|
| Methods in org.encog.neural.networks.training.cpn that return BasicNetwork | |
|---|---|
BasicNetwork |
TrainOutstar.getNetwork()
|
BasicNetwork |
TrainInstar.getNetwork()
|
| Constructors in org.encog.neural.networks.training.cpn with parameters of type BasicNetwork | |
|---|---|
FindCPN(BasicNetwork network)
Construct the object and find the parts of the network. |
|
TrainInstar(BasicNetwork network,
NeuralDataSet training,
double learningRate)
Construct the instar training object. |
|
TrainOutstar(BasicNetwork network,
NeuralDataSet training,
double learningRate)
Construct the outstar trainer. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.cross |
|---|
| Methods in org.encog.neural.networks.training.cross that return BasicNetwork | |
|---|---|
BasicNetwork |
CrossTraining.getNetwork()
|
| Constructors in org.encog.neural.networks.training.cross with parameters of type BasicNetwork | |
|---|---|
CrossTraining(BasicNetwork network,
FoldedDataSet training)
Construct a cross trainer. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.genetic |
|---|
| Methods in org.encog.neural.networks.training.genetic that return BasicNetwork | |
|---|---|
BasicNetwork |
NeuralGeneticAlgorithm.getNetwork()
|
BasicNetwork |
NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper.getNetwork()
Get the current best neural network. |
| 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(NeuralGeneticAlgorithm nga,
BasicNetwork network)
Construct a neural genome. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.hebbian |
|---|
| Methods in org.encog.neural.networks.training.hebbian that return BasicNetwork | |
|---|---|
BasicNetwork |
HebbianTraining.getNetwork()
|
| Constructors in org.encog.neural.networks.training.hebbian with parameters of type BasicNetwork | |
|---|---|
HebbianTraining(BasicNetwork network,
NeuralDataSet training,
boolean oja,
double learningRate)
Construct a Hebbian training object. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.lma |
|---|
| Methods in org.encog.neural.networks.training.lma that return BasicNetwork | |
|---|---|
BasicNetwork |
LevenbergMarquardtTraining.getNetwork()
|
| Constructors in org.encog.neural.networks.training.lma with parameters of type BasicNetwork | |
|---|---|
JacobianChainRule(BasicNetwork network,
Indexable indexableTraining)
Construct the chain rule calculation. |
|
LevenbergMarquardtTraining(BasicNetwork network,
NeuralDataSet training)
Construct the LMA object. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.neat |
|---|
| Methods in org.encog.neural.networks.training.neat that return BasicNetwork | |
|---|---|
BasicNetwork |
NEATTraining.getNetwork()
|
| Constructors in org.encog.neural.networks.training.neat with parameters of type BasicNetwork | |
|---|---|
NEATTraining(CalculateScore score,
BasicNetwork network,
Population population)
Construct a NEAT training object. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.propagation |
|---|
| Methods in org.encog.neural.networks.training.propagation that return BasicNetwork | |
|---|---|
BasicNetwork |
Propagation.getNetwork()
|
| Constructors in org.encog.neural.networks.training.propagation with parameters of type BasicNetwork | |
|---|---|
Propagation(BasicNetwork network,
NeuralDataSet training)
Construct a propagation object. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.propagation.back |
|---|
| Constructors in org.encog.neural.networks.training.propagation.back with parameters of type BasicNetwork | |
|---|---|
Backpropagation(BasicNetwork network,
NeuralDataSet training)
Create a class to train using backpropagation. |
|
Backpropagation(BasicNetwork network,
NeuralDataSet training,
double learnRate,
double momentum)
Train using the specified learning rate and momentum. |
|
Backpropagation(BasicNetwork network,
NeuralDataSet training,
OpenCLTrainingProfile profile,
double learnRate,
double momentum)
|
|
| Uses of BasicNetwork in org.encog.neural.networks.training.propagation.manhattan |
|---|
| Constructors in org.encog.neural.networks.training.propagation.manhattan with parameters of type BasicNetwork | |
|---|---|
ManhattanPropagation(BasicNetwork network,
NeuralDataSet training,
double learnRate)
Construct a Manhattan propagation training object. |
|
ManhattanPropagation(BasicNetwork network,
NeuralDataSet training,
OpenCLTrainingProfile profile,
double learnRate)
Construct a Manhattan propagation training object. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.propagation.resilient |
|---|
| Constructors in org.encog.neural.networks.training.propagation.resilient with parameters of type BasicNetwork | |
|---|---|
ResilientPropagation(BasicNetwork network,
NeuralDataSet training)
Construct a resilient training object. |
|
ResilientPropagation(BasicNetwork network,
NeuralDataSet training,
OpenCLTrainingProfile profile)
Construct an RPROP trainer, allows an OpenCL device to be specified. |
|
ResilientPropagation(BasicNetwork network,
NeuralDataSet training,
OpenCLTrainingProfile profile,
double initialUpdate,
double maxStep)
Construct a resilient training object, allow the training parameters to be specified. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.propagation.scg |
|---|
| Constructors in org.encog.neural.networks.training.propagation.scg with parameters of type BasicNetwork | |
|---|---|
ScaledConjugateGradient(BasicNetwork network,
NeuralDataSet training)
Construct a training class. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.simple |
|---|
| Methods in org.encog.neural.networks.training.simple that return BasicNetwork | |
|---|---|
BasicNetwork |
TrainAdaline.getNetwork()
|
| Constructors in org.encog.neural.networks.training.simple with parameters of type BasicNetwork | |
|---|---|
TrainAdaline(BasicNetwork network,
NeuralDataSet training,
double learningRate)
Construct an ADALINE trainer. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.svd |
|---|
| Methods in org.encog.neural.networks.training.svd that return BasicNetwork | |
|---|---|
BasicNetwork |
SVDTraining.getNetwork()
|
| Constructors in org.encog.neural.networks.training.svd with parameters of type BasicNetwork | |
|---|---|
SVDTraining(BasicNetwork network,
NeuralDataSet training)
Construct the training object. |
|
| Uses of BasicNetwork in org.encog.neural.networks.training.svm |
|---|
| Methods in org.encog.neural.networks.training.svm that return BasicNetwork | |
|---|---|
BasicNetwork |
SVMTrain.getNetwork()
|
| Constructors in org.encog.neural.networks.training.svm with parameters of type BasicNetwork | |
|---|---|
SVMTrain(BasicNetwork network,
NeuralDataSet training)
Construct a trainer for an SVM network. |
|
| Uses of BasicNetwork in org.encog.neural.pattern |
|---|
| Methods in org.encog.neural.pattern that return BasicNetwork | |
|---|---|
BasicNetwork |
SVMPattern.generate()
|
BasicNetwork |
SOMPattern.generate()
Generate the RSOM network. |
BasicNetwork |
RSOMPattern.generate()
Generate the RSOM network. |
BasicNetwork |
RadialBasisPattern.generate()
Generate the RBF network. |
BasicNetwork |
NeuralNetworkPattern.generate()
Generate the specified neural network. |
BasicNetwork |
NEATPattern.generate()
Generate the RBF network. |
BasicNetwork |
JordanPattern.generate()
Generate a Jordan neural network. |
BasicNetwork |
HopfieldPattern.generate()
Generate the Hopfield neural network. |
BasicNetwork |
FeedForwardPattern.generate()
Generate the feedforward neural network. |
BasicNetwork |
ElmanPattern.generate()
Generate the Elman neural network. |
BasicNetwork |
CPNPattern.generate()
Generate the network. |
BasicNetwork |
BoltzmannPattern.generate()
Generate the network. |
BasicNetwork |
BAMPattern.generate()
|
BasicNetwork |
ART1Pattern.generate()
Generate the neural network. |
BasicNetwork |
ADALINEPattern.generate()
Generate the network. |
| 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.util |
|---|
| Methods in org.encog.util with parameters of type BasicNetwork | |
|---|---|
static void |
EncogValidate.validateNetworkForTraining(BasicNetwork network,
NeuralDataSet training)
Validate a network for training. |
| Uses of BasicNetwork in org.encog.util.benchmark |
|---|
| Methods in org.encog.util.benchmark with parameters of type BasicNetwork | |
|---|---|
static int |
Evaluate.evaluateTrain(OpenCLTrainingProfile profile,
BasicNetwork network,
NeuralDataSet 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.evaluate(BasicNetwork network,
NeuralDataSet training)
Evaluate the network and display (to the console) the output for every value in the training set. |
static void |
EncogUtility.trainConsole(BasicNetwork network,
NeuralDataSet trainingSet,
int minutes)
Train the neural network, using SCG training, and output status to the console. |
static void |
EncogUtility.trainConsole(Train train,
BasicNetwork network,
NeuralDataSet trainingSet,
int minutes)
Train the network, using the specified training algorithm, and send the output to the console. |
static void |
EncogUtility.trainDialog(BasicNetwork network,
NeuralDataSet trainingSet)
Train using SCG and display progress to a dialog box. |
static void |
EncogUtility.trainDialog(Train train,
BasicNetwork network,
NeuralDataSet trainingSet)
Train, using the specified training method, display progress to a dialog box. |
static void |
EncogUtility.trainToError(BasicNetwork network,
NeuralDataSet trainingSet,
double error)
Train the network, to a specific error, send the output to the console. |
static void |
EncogUtility.trainToError(Train train,
BasicNetwork network,
NeuralDataSet trainingSet,
double error)
Train to a specific error, using the specified training method, send the output to the console. |
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