Uses of Class
org.neuroph.core.NeuralNetwork

Packages that use NeuralNetwork

Package	Description
org.neuroph.core	Provides base classes and basic building components for neural networks.
org.neuroph.core.events	Provides neural network learning events system
org.neuroph.core.learning	Provides base classes for neural network learning algorithms.
org.neuroph.eval
org.neuroph.eval.classification
org.neuroph.nnet	Provides out-of-the-box neural networks
org.neuroph.nnet.learning	Provides implementations of specific neural network learning algorithms.
org.neuroph.util	Provides various utility classes for creating neural networks, type codes, parsing vectors, etc.
org.neuroph.util.io	Provides input/output adapters for file, JDBC, URL, stream
org.neuroph.util.plugins	Provides various plugins for neural networks.
org.neuroph.util.random	Provides weights randomization techniques

Uses of NeuralNetwork in org.neuroph.core

Methods in org.neuroph.core that return NeuralNetwork

Modifier and Type	Method and Description
static NeuralNetwork	NeuralNetwork.createFromFile(File file) Loads and return s neural network instance from specified file
static NeuralNetwork	NeuralNetwork.createFromFile(String filePath)
NeuralNetwork	Layer.getParentNetwork() Returns reference to parent network
static NeuralNetwork	NeuralNetwork.load(InputStream inputStream) Loads neural network from the specified InputStream.
static NeuralNetwork	NeuralNetwork.load(String filePath) Deprecated. Use createFromFile method instead

Methods in org.neuroph.core with parameters of type NeuralNetwork

Modifier and Type	Method and Description
void	Layer.setParentNetwork(NeuralNetwork parent) Sets reference on parent network

Uses of NeuralNetwork in org.neuroph.core.events

Constructors in org.neuroph.core.events with parameters of type NeuralNetwork

Constructor and Description
NeuralNetworkEvent(NeuralNetwork source, NeuralNetworkEvent.Type eventType)

Uses of NeuralNetwork in org.neuroph.core.learning

Fields in org.neuroph.core.learning declared as NeuralNetwork

Modifier and Type	Field and Description
protected NeuralNetwork<?>	LearningRule.neuralNetwork Neural network to train

Methods in org.neuroph.core.learning that return NeuralNetwork

Modifier and Type	Method and Description
NeuralNetwork	LearningRule.getNeuralNetwork() Gets neural network

Methods in org.neuroph.core.learning with parameters of type NeuralNetwork

Modifier and Type	Method and Description
void	LearningRule.setNeuralNetwork(NeuralNetwork neuralNetwork) Sets neural network for this learning rule

Uses of NeuralNetwork in org.neuroph.eval

Methods in org.neuroph.eval that return NeuralNetwork

Modifier and Type	Method and Description
NeuralNetwork	FoldResult.getNeuralNet() Returns neural network trained in this cross-validation fold.
NeuralNetwork	EvaluationResult.getNeuralNetwork()

Methods in org.neuroph.eval with parameters of type NeuralNetwork

Modifier and Type	Method and Description
EvaluationResult	Evaluation.evaluate(NeuralNetwork neuralNetwork, DataSet testSet) Runs evaluation procedure for given neural network and data set through all evaluatoors Evaluation results are stored in evaluators
static void	Evaluation.runFullEvaluation(NeuralNetwork<?> neuralNet, DataSet dataSet) Out of the box method (util) which computes all metrics for given neural network and test data set
void	EvaluationResult.setNeuralNetwork(NeuralNetwork neuralNetwork)

Constructors in org.neuroph.eval with parameters of type NeuralNetwork

Constructor and Description
CrossValidationBak(NeuralNetwork neuralNetwork, DataSet dataSet, int foldCount) Creates a new instance of crrossvalidation for specified neural network, data set and number of folds.
FoldResult(NeuralNetwork neuralNet, DataSet trainingSet, DataSet validationSet)
KFoldCrossValidation(NeuralNetwork neuralNetwork, DataSet dataSet, int numFolds)

Uses of NeuralNetwork in org.neuroph.eval.classification

Methods in org.neuroph.eval.classification with parameters of type NeuralNetwork

Modifier and Type	Method and Description
boolean	McNemarTest.evaluateNetworks(NeuralNetwork network1, NeuralNetwork network2, DataSet dataSet)
boolean	McNemarTest.evaluateNetworks(NeuralNetwork network1, NeuralNetwork network2, DataSet dataSet)

Uses of NeuralNetwork in org.neuroph.nnet

Subclasses of NeuralNetwork in org.neuroph.nnet

Modifier and Type	Class and Description
class	Adaline Adaline neural network architecture with LMS learning rule.
class	AutoencoderNetwork Auto Encoder Neural Network
class	BAM Bidirectional Associative Memory
class	CompetitiveNetwork Two layer neural network with competitive learning rule.
class	ConvolutionalNetwork Convolutional neural network with backpropagation algorithm modified for convolutional networks.
class	ElmanNetwork Under development: Learning rule BackProp Through Time required
class	Hopfield Hopfield neural network.
class	Instar Instar neural network with Instar learning rule.
class	JordanNetwork Under development: Learning rule BackProp Through Time required
class	Kohonen Kohonen neural network.
class	MaxNet Max Net neural network with competitive learning rule.
class	MultiLayerPerceptron Multi Layer Perceptron neural network with Back propagation learning algorithm.
class	NeuroFuzzyPerceptron The NeuroFuzzyReasoner class represents Neuro Fuzzy Reasoner architecture.
class	Outstar Outstar neural network with Outstar learning rule.
class	Perceptron Perceptron neural network with some LMS based learning algorithm.
class	RBFNetwork Radial basis function neural network.
class	RectifierNeuralNetwork
class	SupervisedHebbianNetwork Hebbian neural network with supervised Hebbian learning algorithm.
class	UnsupervisedHebbianNetwork Hebbian neural network with unsupervised Hebbian learning algorithm.

Uses of NeuralNetwork in org.neuroph.nnet.learning

Methods in org.neuroph.nnet.learning that return NeuralNetwork

Modifier and Type	Method and Description
NeuralNetwork	SimulatedAnnealingLearning.getNetwork() Get the best network from the training.

Methods in org.neuroph.nnet.learning with parameters of type NeuralNetwork

Modifier and Type	Method and Description
void	KohonenLearning.setNeuralNetwork(NeuralNetwork neuralNetwork)

Constructors in org.neuroph.nnet.learning with parameters of type NeuralNetwork

Constructor and Description
SimulatedAnnealingLearning(NeuralNetwork network)
SimulatedAnnealingLearning(NeuralNetwork network, double startTemp, double stopTemp, int cycles) Construct a simulated annleaing trainer for a feedforward neural network.

Uses of NeuralNetwork in org.neuroph.util

Methods in org.neuroph.util with parameters of type NeuralNetwork

Modifier and Type	Method and Description
static void	NeuralNetworkCODEC.array2network(double[] array, NeuralNetwork network) Decode a network from an array.
static int	NeuralNetworkCODEC.determineArraySize(NeuralNetwork network) Determine the array size for the given neural network.
static void	NeuralNetworkCODEC.network2array(NeuralNetwork network, double[] array) Encode a network to an array.
static void	NeuralNetworkFactory.setDefaultIO(NeuralNetwork nnet) Sets default input and output neurons for network (first layer as input, last as output)

Uses of NeuralNetwork in org.neuroph.util.io

Methods in org.neuroph.util.io with parameters of type NeuralNetwork

Modifier and Type	Method and Description
static void	IOHelper.process(NeuralNetwork neuralNet, InputAdapter in, OutputAdapter out) Feeds specified neural network with data from InputAdapter and writes output using OutputAdapter

Uses of NeuralNetwork in org.neuroph.util.plugins

Methods in org.neuroph.util.plugins that return NeuralNetwork

Modifier and Type	Method and Description
NeuralNetwork<?>	PluginBase.getParentNetwork() Returns the parent network for this plugin

Methods in org.neuroph.util.plugins with parameters of type NeuralNetwork

Modifier and Type	Method and Description
void	PluginBase.setParentNetwork(NeuralNetwork parentNetwork) Sets the parent network for this plugin

Uses of NeuralNetwork in org.neuroph.util.random

Methods in org.neuroph.util.random with parameters of type NeuralNetwork

Modifier and Type	Method and Description
void	NguyenWidrowRandomizer.randomize(NeuralNetwork neuralNetwork)
void	WeightsRandomizer.randomize(NeuralNetwork<?> neuralNetwork) Iterates and randomizes all layers in specified network