Uses of Class
yawn.util.Pattern

Packages that use Pattern

yawn.envs
yawn.envs.delve
yawn.envs.plaintext
yawn.envs.synthetic
yawn.nn
yawn.nn.appart
yawn.nn.committee
yawn.nn.committee.functions
yawn.nn.fuzzyartmap
yawn.nn.gasart
yawn.nn.mlp
yawn.nn.mlp.smart
yawn.optim.genetic
yawn.util

Uses of Pattern in yawn.envs

Methods in yawn.envs that return Pattern

abstract Pattern[]

Environment.getTestDatasetInputs(int runNumber) Reads a test dataset from the environment.

Methods in yawn.envs with parameters of type Pattern

abstract void

Environment.writeResults(Pattern[] results, int runNumber)

Uses of Pattern in yawn.envs.delve

Methods in yawn.envs.delve that return Pattern

Pattern[]

DelveEnvironment.getTestDatasetInputs(int runNumber) Reads a test data file from a DELVE directory.

Methods in yawn.envs.delve with parameters of type Pattern

void	DelveEnvironment.writeResults(Pattern[] results, int runNumber) Writes a DELVE cguess file representing the predictions of a neural network.

Uses of Pattern in yawn.envs.plaintext

Methods in yawn.envs.plaintext that return Pattern

Pattern[]

PlainTextEnvironment.getTestDatasetInputs(int runNumber)

Methods in yawn.envs.plaintext with parameters of type Pattern

void	PlainTextEnvironment.writeResults(Pattern[] results, int runNumber) Writes the results to a an ascii file.

Uses of Pattern in yawn.envs.synthetic

Fields in yawn.envs.synthetic declared as Pattern

protected Pattern

CircleInTheSquareEnvironment.center

Methods in yawn.envs.synthetic that return Pattern

protected Pattern	XOrDataEnvironment.generateRandomInput()
protected abstract Pattern	SyntheticDataEnvironment.generateRandomInput()
protected Pattern	CircleInTheSquareEnvironment.generateRandomInput()
Pattern[]	SyntheticDataEnvironment.getTestDatasetInputs(int runNumber)
Pattern[]	SyntheticDataEnvironment.getTestExpectedOutputsSet(int runNumber)
protected Pattern	XOrDataEnvironment.synthetizeOutput(Pattern input) (non-Javadoc)
protected abstract Pattern	SyntheticDataEnvironment.synthetizeOutput(Pattern input)
protected Pattern	CircleInTheSquareEnvironment.synthetizeOutput(Pattern input)

Methods in yawn.envs.synthetic with parameters of type Pattern

protected Pattern	XOrDataEnvironment.synthetizeOutput(Pattern input) (non-Javadoc)
protected abstract Pattern	SyntheticDataEnvironment.synthetizeOutput(Pattern input)
protected Pattern	CircleInTheSquareEnvironment.synthetizeOutput(Pattern input)
void	SyntheticDataEnvironment.writeResults(Pattern[] results, int runNumber)

Uses of Pattern in yawn.nn

Fields in yawn.nn declared as Pattern

protected Pattern	NeuralNode.input
protected Pattern	InputLayer.input

Methods in yawn.nn that return Pattern

protected Pattern	Layer.getActivations()
protected Pattern	InputLayer.getActivations()
Pattern	Layer.output()
abstract Pattern	NeuralNetwork.predict(Pattern input) Computes a network prediction

Methods in yawn.nn with parameters of type Pattern

protected abstract double	NeuralNode.activationFunction(Pattern input)
abstract void	NeuralNetwork.oneLearningStep(Pattern input, Pattern output) Performs one learning iteration.
abstract Pattern	NeuralNetwork.predict(Pattern input) Computes a network prediction
void	NeuralNode.setInput(Pattern val) sets the current input of the node
void	Layer.setInput(Pattern input)
void	InputLayer.setInput(Pattern p)

Uses of Pattern in yawn.nn.appart

Fields in yawn.nn.appart declared as Pattern

protected Pattern	AppArtConfig.initialDeviations
protected Pattern	AppArt.initialDeviations
protected Pattern	RadialBasisFunctionsNeuralNode.lambda
protected Pattern	RadialBasisFunctionsNeuralNode.mu
protected Pattern	RecognitionLayer.normalizedActivations
protected Pattern	RadialBasisFunctionsNeuralNode.sigma
protected Pattern	PredictionNeuralNode.weights

Methods in yawn.nn.appart that return Pattern

Pattern	AppArtConfig.getInitialDeviations()
Pattern	AppArt.getInitialDeviations()
Pattern	RadialBasisFunctionsNeuralNode.getLambda()
Pattern	RadialBasisFunctionsNeuralNode.getMu()
Pattern	RecognitionLayer.getNormalizedActivations()
Pattern	RadialBasisFunctionsNeuralNode.getSigma()
Pattern	PredictionNeuralNode.getWeights()
protected Pattern	AppArt.learnNewCategory(Pattern output)
Pattern	AppArt.predict(Pattern input)
protected Pattern	AppArt.propagate(Pattern output) Propagates the input already already presented to the network (by calling setInput())

Methods in yawn.nn.appart with parameters of type Pattern

protected double	RadialBasisFunctionsNeuralNode.activationFunction(Pattern input)
protected double	PredictionNeuralNode.activationFunction(Pattern input)
protected double	RadialBasisFunctionsNeuralNode.bigG(Pattern input)
void	GainControlUnitOnOutput.calculateAbsoluteError(Pattern o, Pattern y)
void	GainControlUnitOnOutput.calculateRelativeError(Pattern o, Pattern y)
protected void	AppArt.computeError(Pattern prediction, Pattern expected)
void	PredictionLayer.learn(Pattern y)
protected void	AppArt.learn(Pattern pat)
protected Pattern	AppArt.learnNewCategory(Pattern output)
void	RadialBasisFunctionsNeuralNode.learnNewClass(Pattern gamma, int n) Sets up the node to exactly represents the class specified by the current input.
protected double	RadialBasisFunctionsNeuralNode.netInput(Pattern input)
void	AppArt.oneLearningStep(Pattern input, Pattern output)
Pattern	AppArt.predict(Pattern input)
protected Pattern	AppArt.propagate(Pattern output) Propagates the input already already presented to the network (by calling setInput())
void	AppArtConfig.setInitialDeviations(Pattern initialDeviations)
void	AppArt.setInitialDeviations(Pattern initialDeviations)
void	RecognitionLayer.setInput(Pattern input)
void	PredictionLayer.setInput(Pattern input)
void	AppArt.setInput(Pattern input)
void	RadialBasisFunctionsNeuralNode.setLambda(Pattern lambda)
void	RadialBasisFunctionsNeuralNode.setMu(Pattern mu)
void	RadialBasisFunctionsNeuralNode.setSigma(Pattern sigma)
void	PredictionNeuralNode.setWeights(Pattern weights)
void	PredictionLayer.updateWeightsStructure(Pattern y)

Uses of Pattern in yawn.nn.committee

Methods in yawn.nn.committee that return Pattern

Pattern

NetworkCommittee.predict(Pattern input)

Methods in yawn.nn.committee with parameters of type Pattern

void	NetworkCommittee.oneLearningStep(Pattern input, Pattern output) this has no sense in this context, throws an UnsupportedOperationException by default.
Pattern	NetworkCommittee.predict(Pattern input)

Uses of Pattern in yawn.nn.committee.functions

Methods in yawn.nn.committee.functions that return Pattern

Pattern	Popularity.assamble(Pattern[] x)
Pattern	CommitteeFunction.assamble(Pattern[] x) Builds a committe response from an array of outputs.

Methods in yawn.nn.committee.functions with parameters of type Pattern

Pattern	Popularity.assamble(Pattern[] x)
Pattern	CommitteeFunction.assamble(Pattern[] x) Builds a committe response from an array of outputs.

Uses of Pattern in yawn.nn.fuzzyartmap

Methods in yawn.nn.fuzzyartmap that return Pattern

protected Pattern	FuzzyArtMap.bThenAActivation(Pattern input, Pattern output) Activates ARTb before ARTa, this kind of activation avoids the ``match tracking anomaly'' reported in
Pattern	FuzzyArtMap.deScaleZeroOneOutput(Pattern pat)
Pattern	FuzzyArtMap.predict(Pattern input)
Pattern	FuzzyArtMap.scaleZeroOneInput(Pattern pat)

Methods in yawn.nn.fuzzyartmap with parameters of type Pattern

protected Pattern	FuzzyArtMap.bThenAActivation(Pattern input, Pattern output) Activates ARTb before ARTa, this kind of activation avoids the ``match tracking anomaly'' reported in
Pattern	FuzzyArtMap.deScaleZeroOneOutput(Pattern pat)
void	FuzzyArtMap.oneLearningStep(Pattern input, Pattern output)
Pattern	FuzzyArtMap.predict(Pattern input)
Pattern	FuzzyArtMap.scaleZeroOneInput(Pattern pat)

Uses of Pattern in yawn.nn.gasart

Fields in yawn.nn.gasart declared as Pattern

protected Pattern

GasRecognitionNode.defaultSigma

Methods in yawn.nn.gasart that return Pattern

Pattern	GasArt.learnNewCategory(Pattern p)
Pattern	GasRecognitionNode.position()

Methods in yawn.nn.gasart with parameters of type Pattern

protected double	GasRecognitionNode.activationFuntion(Pattern input)
void	GasArt.learn(Pattern p)
Pattern	GasArt.learnNewCategory(Pattern p)
void	GasRecognitionNode.learnNewClass(Pattern gamma, int n)
GasRecognitionNode	GasArt.makeFstSndBMUConexion(Pattern p)

Uses of Pattern in yawn.nn.mlp

Fields in yawn.nn.mlp declared as Pattern

protected Pattern	PerceptronNode.momentum
protected Pattern	PerceptronNode.weights

Methods in yawn.nn.mlp that return Pattern

Pattern	MLPLayer.calculateDeltasAsHiddenLayer(Pattern nextLayerDeltas)
Pattern	MLPLayer.calculateDeltasAsOutputLayer(Pattern expectedOutputs)
Pattern	PerceptronNode.getWeights()
Pattern	MultiLayerPerceptron.predict(Pattern input)

Methods in yawn.nn.mlp with parameters of type Pattern

protected double	PerceptronNode.activationFunction(Pattern input)
void	MLPLayer.adapt(Pattern deltas, double learningRate, double momentumRate)
Pattern	MLPLayer.calculateDeltasAsHiddenLayer(Pattern nextLayerDeltas)
Pattern	MLPLayer.calculateDeltasAsOutputLayer(Pattern expectedOutputs)
double	PerceptronNode.calculateHiddenLayerDelta(Pattern nextLayerDeltas, Pattern nextLayerWeights) Calculate the deltas using the subsequent layer deltas and the weights emmanent from this node.
void	MultiLayerPerceptron.oneLearningStep(Pattern input, Pattern output) Implements a learning iteration as: propagates the input storing the activation of all nodes; sums in errorSum the mean square error of the prediction; calculation of the deltas; backpropagation of errors, and; weights update.
Pattern	MultiLayerPerceptron.predict(Pattern input)
void	MLPLayer.setInput(Pattern input) Does the `threshold as weight' trick.
void	PerceptronNode.setWeights(Pattern weights)

Uses of Pattern in yawn.nn.mlp.smart

Methods in yawn.nn.mlp.smart that return Pattern

Pattern

SmartMultiLayerPerceptron.predict(Pattern input)

Methods in yawn.nn.mlp.smart with parameters of type Pattern

void	SmartMultiLayerPerceptron.oneLearningStep(Pattern input, Pattern output)
Pattern	SmartMultiLayerPerceptron.predict(Pattern input)

Uses of Pattern in yawn.optim.genetic

Methods in yawn.optim.genetic that return Pattern

Pattern

GeneticParameterFitter.predict(Pattern input)

Methods in yawn.optim.genetic with parameters of type Pattern

void	GeneticParameterFitter.oneLearningStep(Pattern input, Pattern output)
Pattern	GeneticParameterFitter.predict(Pattern input)

Uses of Pattern in yawn.util

Fields in yawn.util declared as Pattern

Pattern	InputOutputPattern.input
Pattern	InputOutputPattern.output

Methods in yawn.util that return Pattern

Pattern	Pattern.add(double operand) Scalar addition.
Pattern	Pattern.add(Pattern operand) Element-wise addition.
protected Pattern[]	DefaultStatisticsFacility.getPredictions(NeuralNetwork net, InputOutputPattern[] set)
Pattern	Pattern.multiply(double operand) Scalar multipication.
static Pattern	Pattern.parsePattern(java.lang.String str) Parses a String into a Pattern.
Pattern	Pattern.substract(Pattern operand)

Methods in yawn.util with parameters of type Pattern

Pattern	Pattern.add(Pattern operand) Element-wise addition.
protected static void	ErrorUtils.checkDimensions(Pattern[] desired, Pattern[] predictions)
protected static void	ErrorUtils.checkDimensions(Pattern[] desired, Pattern[] predictions)
protected void	Pattern.checkEqualSize(Pattern comp) Checks if a Pattern has equal size.
double	Pattern.dist(Pattern other) Calculates an Euclidean distance from this Pattern.
boolean	Pattern.equals(Pattern other)
double	Pattern.innerProduct(Pattern operand) Calculates the inner product of two Patterns.
double	DefaultStatisticsFacility.meanSquaredError(InputOutputPattern[] set, Pattern[] predictions)
static double	ErrorUtils.meanSquaredError(Pattern[] desired, Pattern[] predictions)
static double	ErrorUtils.meanSquaredError(Pattern[] desired, Pattern[] predictions)
void	Pattern.setComponents(Pattern orig) Sets elements to the ones of orig.
Pattern	Pattern.substract(Pattern operand)

Constructors in yawn.util with parameters of type Pattern

Pattern(Pattern source)
Creates a Pattern whose elements are copied from source.