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## G

Gaussian - Class in org.neuroph.core.transfer
  Gaussian neuron transfer function.
Gaussian() - Constructor for class org.neuroph.core.transfer.Gaussian
  Creates an instance of Gaussian neuron transfer
Gaussian(Properties) - Constructor for class org.neuroph.core.transfer.Gaussian
  Creates an instance of Gaussian neuron transfer function with the specified properties.
GenerateSet - Class in org.neuroph.samples.timeseries
  Very simple basic class which wraps the data generation process for the Time-Series Prediction tutorial.
GenerateSet(String, boolean, int, int) - Constructor for class org.neuroph.samples.timeseries.GenerateSet
  Contructor for datase set generator which takes filename and data set settings as arguments
GenerateSineWave - Class in org.neuroph.samples.timeseries
  Very simple class which just wraps up the generation of a sine wave at one degree steps.
GenerateTrainingSets - Class in org.neuroph.samples.timeseries
  Very simple class which just wraps up the generation of the time-series predicition training sets.
GenerateTrainingSets() - Constructor for class org.neuroph.samples.timeseries.GenerateTrainingSets
getBias() - Method in class org.neuroph.nnet.comp.InputOutputNeuron
  Returns bias value for this neuron
getBlueValues() - Method in class org.neuroph.contrib.imgrec.FractionRgbData
  Returns blue color component for the entire image
getColorMode() - Method in class org.neuroph.contrib.imgrec.ImageRecognitionPlugin
  Returns color mode used for image recognition
getColorMode() - Method in class org.neuroph.contrib.ocr.OcrPlugin
  Returns color mode used for OCR
getConnectedNeuron() - Method in class org.neuroph.core.Connection
  Returns the connected neuron of this connection
getConnectionFrom(Neuron) - Method in class org.neuroph.core.Neuron
  Gets input connection from the specified neuron * @param fromNeuron neuron connected to this neuron as input
getConnectionsFromOtherLayers() - Method in class org.neuroph.nnet.comp.CompetitiveNeuron
  Returns collection of connections from other layers
getCurrentIteration() - Method in class org.neuroph.core.learning.IterativeLearning
  Returns current iteration of this learning algorithm
getDelay() - Method in class org.neuroph.nnet.comp.DelayedConnection
  Returns delay value for this connection
getDerivative(double) - Method in class org.neuroph.core.transfer.Gaussian
getDerivative(double) - Method in class org.neuroph.core.transfer.Linear
getDerivative(double) - Method in class org.neuroph.core.transfer.Sigmoid
getDerivative(double) - Method in class org.neuroph.core.transfer.Tanh
getDerivative(double) - Method in class org.neuroph.core.transfer.TransferFunction
  Returns the first derivative of this function.
getDesiredOutput() - Method in class org.neuroph.core.learning.SupervisedTrainingElement
  Returns desired output for this training element
getError() - Method in class org.neuroph.core.Neuron
  Returns error for this neuron.
getErrorCorrection() - Method in class org.neuroph.nnet.learning.BinaryDeltaRule
  Gets the errorCorrection parametar
getFilePath() - Method in class org.neuroph.core.learning.TrainingSet
  Returns full file path for this training set
getFlattenedRgbValues() - Method in class org.neuroph.contrib.imgrec.FractionRgbData
  Returns rgb data in a form: all red rows, all green rows, all blue rows
getFractionRgbDataForImages(HashMap<String, BufferedImage>) - Static method in class org.neuroph.contrib.ocr.OcrUtils
  Returns RGB data for all input images
getGreenValues() - Method in class org.neuroph.contrib.imgrec.FractionRgbData
  Returns green color component for the entire image
getHeight() - Method in class org.neuroph.contrib.imgrec.FractionRgbData
  Get image height
getInput() - Method in class org.neuroph.core.Connection
  Returns input received through this connection - the activation that comes from the output of the cell on the other end of connection
getInput() - Method in class org.neuroph.core.learning.TrainingElement
  Returns input vector
getInput() - Method in class org.neuroph.nnet.comp.DelayedConnection
  Gets delayed input through this connection
getInputConnections() - Method in class org.neuroph.core.Neuron
  Returns input connections for this neuron as Vector collection
getInputFunction() - Method in class org.neuroph.core.Neuron
  Returns input function
getInputNeurons() - Method in class org.neuroph.core.NeuralNetwork
  Gets reference to input neurons Vector.
getInputsIterator() - Method in class org.neuroph.core.Neuron
  Returns Iterator interface for accessing input connections
getIteration() - Method in class org.neuroph.nnet.learning.KohonenLearning
getLabel() - Method in class org.neuroph.core.learning.TrainingElement
  Get training element label
getLabel() - Method in class org.neuroph.core.learning.TrainingSet
  Returns label for this training set
getLabel(Object) - Method in class org.neuroph.util.plugins.LabelsPlugin
  Returns label for the specified object
getLayerAt(int) - Method in class org.neuroph.core.NeuralNetwork
  Returns layer at specified index
getLayers() - Method in class org.neuroph.core.NeuralNetwork
  Returns getLayersIterator Vector collection
getLayersCount() - Method in class org.neuroph.core.NeuralNetwork
  Returns number of layers in network
getLayersIterator() - Method in class org.neuroph.core.NeuralNetwork
  Returns interface for iterating layers
getLearningRate() - Method in class org.neuroph.core.learning.IterativeLearning
  Returns learning rate for this algorithm
getLearningRate() - Method in class org.neuroph.nnet.learning.KohonenLearning
getLearningRateChange() - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
getLearningRule() - Method in class org.neuroph.core.NeuralNetwork
  Returns the learning algorithm of this network
getLearningThread() - Method in class org.neuroph.core.NeuralNetwork
  Returns the current learning thread (if it is learning in the new thread Check what happens if it learns in the same thread)
getLeftHigh() - Method in class org.neuroph.core.transfer.Trapezoid
  Returns left high point of trapezoid function
getLeftLow() - Method in class org.neuroph.core.transfer.Trapezoid
  Returns left low point of trapezoid function
getMapSize() - Method in class org.neuroph.nnet.learning.KohonenLearning
getMaxCounter() - Method in class org.neuroph.samples.stockmarket.StockFileReader
getMaxCounter() - Method in class org.neuroph.samples.stockmarket.StockSocketReader
getMaxError() - Method in class org.neuroph.core.learning.SupervisedLearning
  Returns learning error tolerance - the value of total network error to stop learning.
getMaxIterations() - Method in class org.neuroph.nnet.comp.CompetitiveLayer
  Returns the maxIterations setting for this layer
getMaxLearningRate() - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
getMaxMomentum() - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
getMaxOutput() - Method in class org.neuroph.contrib.imgrec.ImageRecognitionPlugin
  Returns one or more image labels with the maximum output - recognized images
getMinErrorChange() - Method in class org.neuroph.core.learning.SupervisedLearning
  Returns min error change stopping criteria
getMinErrorChangeIterationsCount() - Method in class org.neuroph.core.learning.SupervisedLearning
  Returns number of iterations count for for min error change stopping criteria
getMinErrorChangeIterationsLimit() - Method in class org.neuroph.core.learning.SupervisedLearning
  Returns number of iterations for min error change stopping criteria
getMinLearningRate() - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
getMinMomentum() - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
getMomentum() - Method in class org.neuroph.nnet.learning.MomentumBackpropagation
  Returns the momentum factor
getMomentumChange() - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
getName() - Method in class org.neuroph.util.plugins.PluginBase
  Returns the name of this plugin
getNetInput() - Method in class org.neuroph.core.Neuron
  Returns total net input
getNetwork(String) - Method in class org.neuroph.nnet.ModularNetwork
  Gets neural network
getNetworkType() - Method in class org.neuroph.core.NeuralNetwork
  Returns type of this network
getNeuralNetwork() - Method in class org.neuroph.core.learning.LearningRule
  Gets neural network
getNeuronAt(int) - Method in class org.neuroph.core.Layer
  Returns neuron at specified index position in this layer
getNeurons() - Method in class org.neuroph.core.Layer
  Returns collection of neurons in this layer
getNeuronsCount() - Method in class org.neuroph.core.Layer
  Returns number of neurons in this layer
getNeuronsIterator() - Method in class org.neuroph.core.Layer
  Returns interface for iterating neurons in this layer
getNeuronType() - Method in class org.neuroph.util.NeuronProperties
getNextSample() - Method in class org.neuroph.samples.timeseries.GenerateSineWave
  Gets next sampling value for the sine wave
getNormalizer() - Method in class org.neuroph.samples.stockmarket.TrainingData
getOutConnections() - Method in class org.neuroph.core.Neuron
  Returns output connections from this neuron
getOutput(double, double) - Method in class org.neuroph.contrib.IACFunction
getOutput(double) - Method in class org.neuroph.contrib.IACFunction
getOutput() - Method in class org.neuroph.contrib.imgrec.ImageRecognitionPlugin
  Returns image recognition result as map with image labels as keys and recogition result as value
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.And
getOutput(Vector<Connection>) - Method in class org.neuroph.core.input.Diference
getOutput(Vector<Connection>) - Method in class org.neuroph.core.input.InputFunction
  Returns ouput value of this input function for the given neuron inputs
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.Intensity
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.Max
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.Min
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.Or
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.Product
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.Sum
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.SummingFunction
  Returns summing function output
getOutput(Vector<Double>) - Method in class org.neuroph.core.input.SumSqr
getOutput(Vector<Connection>) - Method in class org.neuroph.core.input.WeightedInput
  Returns weighted input vector.
getOutput(Vector<Connection>) - Method in class org.neuroph.core.input.WeightsFunction
  Returns function's output
getOutput() - Method in class org.neuroph.core.NeuralNetwork
  Returns network output Vector.
getOutput() - Method in class org.neuroph.core.Neuron
  Returns neuron's output
getOutput(double) - Method in class org.neuroph.core.transfer.Gaussian
getOutput(double) - Method in class org.neuroph.core.transfer.Linear
getOutput(double) - Method in class org.neuroph.core.transfer.Ramp
getOutput(double) - Method in class org.neuroph.core.transfer.Sgn
  y = 1, x > 0 y = -1, x <= 0
getOutput(double) - Method in class org.neuroph.core.transfer.Sigmoid
getOutput(double) - Method in class org.neuroph.core.transfer.Step
getOutput(double) - Method in class org.neuroph.core.transfer.Tanh
getOutput(double) - Method in class org.neuroph.core.transfer.TransferFunction
  Returns the ouput of this function.
getOutput(double) - Method in class org.neuroph.core.transfer.Trapezoid
getOutput() - Method in class org.neuroph.nnet.comp.BiasNeuron
getOutput(int) - Method in class org.neuroph.nnet.comp.DelayedNeuron
  Returns neuron output with the specified delay
getOutputAsArray() - Method in class org.neuroph.core.NeuralNetwork
  Returns network output vector as double array
getOutputNeurons() - Method in class org.neuroph.core.NeuralNetwork
  Returns reference to output neurons Vector.
getParentLayer() - Method in class org.neuroph.core.Neuron
  Returns reference to parent layer for this neuron
getParentNetwork() - Method in class org.neuroph.core.Layer
  Returns reference to parent network
getParentNetwork() - Method in class org.neuroph.util.plugins.PluginBase
  Returns the parent network for this plugin
getPatternError(Vector<Double>, Vector<Double>) - Method in class org.neuroph.core.learning.SupervisedLearning
  Calculates the network error for the current pattern - diference between desired and actual output
getPlugin(String) - Method in class org.neuroph.core.NeuralNetwork
  Returns the requested plugin
getPreviousEpochError() - Method in class org.neuroph.core.learning.SupervisedLearning
  Returns total network error in previous learning epoch
getPreviousValue() - Method in class org.neuroph.core.Weight
  Returns previous weight value
getProperties() - Method in class org.neuroph.core.transfer.Sgn
  Returns the properties of this function
getProperties() - Method in class org.neuroph.core.transfer.Step
  Returns the properties of this function
getProperty(String) - Method in class org.neuroph.util.Properties
getRedValues() - Method in class org.neuroph.contrib.imgrec.FractionRgbData
  Returns red color component for the entire image
getRightHigh() - Method in class org.neuroph.core.transfer.Trapezoid
  Returns right high point of trapezoid function
getRightLow() - Method in class org.neuroph.core.transfer.Trapezoid
  Returns right low point of trapezoid function
getSamplingResolution() - Method in class org.neuroph.contrib.imgrec.ImageRecognitionPlugin
  Returns image sampling resolution (dimensions)
getSamplingResolution() - Method in class org.neuroph.contrib.ocr.OcrPlugin
  Returns sampling resolution used for OCR
getSigma() - Method in class org.neuroph.core.transfer.Gaussian
  Returns the sigma parametar of this function
getSlope() - Method in class org.neuroph.core.transfer.Linear
  Returns the slope parametar of this function
getSlope() - Method in class org.neuroph.core.transfer.Sigmoid
  Returns the slope parametar of this function
getSlope() - Method in class org.neuroph.core.transfer.Tanh
  Returns the slope parametar of this function
getSummingFunction() - Method in class org.neuroph.core.input.InputFunction
  Returns summing function component of this InputFunction
getSummingFunction() - Method in class org.neuroph.util.NeuronProperties
getThresh() - Method in class org.neuroph.nnet.comp.ThresholdNeuron
  Returns threshold value for this neuron
getTotalNetworkError() - Method in class org.neuroph.core.learning.SupervisedLearning
  Returns total network error in current learning epoch
getTrainingSet() - Method in class org.neuroph.core.learning.LearningRule
  Gets training set
getTrainingSet() - Method in class org.neuroph.samples.stockmarket.TrainingData
getTransferFunction() - Method in class org.neuroph.core.Neuron
  Returns transfer function
getTransferFunction() - Method in class org.neuroph.util.NeuronProperties
getTransferFunctionProperties() - Method in class org.neuroph.util.NeuronProperties
getTsleep() - Method in class org.neuroph.samples.stockmarket.StockSocketReader
getTypeClass() - Method in enum org.neuroph.util.SummingFunctionType
getTypeClass() - Method in enum org.neuroph.util.TransferFunctionType
getTypeClass() - Method in enum org.neuroph.util.WeightsFunctionType
getTypeLabel() - Method in enum org.neuroph.util.NeuralNetworkType
getTypeLabel() - Method in enum org.neuroph.util.SummingFunctionType
getTypeLabel() - Method in enum org.neuroph.util.TransferFunctionType
getTypeLabel() - Method in enum org.neuroph.util.WeightsFunctionType
getUseDynamicLearningRate() - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
getUseDynamicMomentum() - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
getValue() - Method in class org.neuroph.core.Weight
  Returns weight value
getValuesRow() - Method in class org.neuroph.samples.stockmarket.StockFileReader
getValuesRow() - Method in class org.neuroph.samples.stockmarket.StockSocketReader
getValuesRow() - Method in class org.neuroph.samples.stockmarket.TrainingData
getWeight() - Method in class org.neuroph.core.Connection
  Returns weight for this connection
getWeightedInput() - Method in class org.neuroph.core.Connection
  Returns the weighted input received through this connection
getWeightsFunction() - Method in class org.neuroph.core.input.InputFunction
  Returns weights functioncomponent of this InputFunction
getWeightsFunction() - Method in class org.neuroph.util.NeuronProperties
getWeightsVector() - Method in class org.neuroph.core.Neuron
  Returns weights vector of input connections
getWidth() - Method in class org.neuroph.contrib.imgrec.FractionRgbData
  Get image width
getWinner() - Method in class org.neuroph.nnet.comp.CompetitiveLayer
  Returns the winning neuron for this layer
getXHigh() - Method in class org.neuroph.core.transfer.Ramp
  Returns threshold value for the high output level
getXLow() - Method in class org.neuroph.core.transfer.Ramp
  Returns threshold value for the low output level
getYHigh() - Method in class org.neuroph.core.transfer.Ramp
  Returns output value for high output level
getYHigh() - Method in class org.neuroph.core.transfer.Step
  Returns output value for high output level
getYLow() - Method in class org.neuroph.core.transfer.Ramp
  Returns output value for low output level
getYLow() - Method in class org.neuroph.core.transfer.Step
  Returns output value for low output level
greenValues - Variable in class org.neuroph.contrib.imgrec.FractionRgbData
  Array which contains green componenet of the color for each image pixel

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