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## S

save(String) - Method in class org.neuroph.core.learning.TrainingSet
  Saves this training set to the specified file
save() - Method in class org.neuroph.core.learning.TrainingSet
  Saves this training set to file specified in its filePath field
save(String) - Method in class org.neuroph.core.NeuralNetwork
  Saves neural network into the specified file.
scanLocationUsingSampling(Robot, Rectangle2D.Double, Dimension) - Static method in class org.neuroph.contrib.imgrec.ImageSampler
  Scans screen location using sampling
scanLocationUsingSampling(Robot, Rectangle2D.Double, Dimension, int) - Static method in class org.neuroph.contrib.imgrec.ImageSampler
  Scans screen location using sampling
scanLocationUsingScreenshot(Robot, Rectangle2D.Double, Dimension) - Static method in class org.neuroph.contrib.imgrec.ImageSampler
  Scans screen location using screenshot
scanLocationUsingScreenshot(Robot, Rectangle2D.Double, Dimension, int) - Static method in class org.neuroph.contrib.imgrec.ImageSampler
  Scans screen location using screenshot
setBias(double) - Method in class org.neuroph.nnet.comp.InputOutputNeuron
  Sets bias value for this neuron
setDefaultIO(NeuralNetwork) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Sets default input and output neurons for network (first layer as input, last as output)
setDelay(int) - Method in class org.neuroph.nnet.comp.DelayedConnection
  Sets delay value for this connection
setDesiredOutput(Vector<Double>) - Method in class org.neuroph.core.learning.SupervisedTrainingElement
  Sets desired output vector for this training element
setError(double) - Method in class org.neuroph.core.Neuron
  Sets error for this neuron.
setErrorCorrection(double) - Method in class org.neuroph.nnet.learning.BinaryDeltaRule
  Sets the errorCorrection parametar
setFilePath(String) - Method in class org.neuroph.core.learning.TrainingSet
  Sets full file path for this training set
setInput(double) - Method in class org.neuroph.contrib.IACNeuron
  Sets total net input for this cell
setInput(BufferedImage) - Method in class org.neuroph.contrib.imgrec.ImageRecognitionPlugin
  Sets network input (image to recognize) from the specified BufferedImage object
setInput(File) - Method in class org.neuroph.contrib.imgrec.ImageRecognitionPlugin
  Sets network input (image to recognize) from the specified File object
setInput(URL) - Method in class org.neuroph.contrib.imgrec.ImageRecognitionPlugin
  Sets network input (image to recognize) from the specified URL object
setInput(Vector<Double>) - Method in class org.neuroph.core.learning.TrainingElement
  Sets input vector
setInput(Vector<Double>) - Method in class org.neuroph.core.NeuralNetwork
  Sets network input.
setInput(double...) - Method in class org.neuroph.core.NeuralNetwork
  Sets network input.
setInput(double) - Method in class org.neuroph.core.Neuron
  Sets neuron's input
setInput(double) - Method in class org.neuroph.nnet.comp.InputOutputNeuron
  Sets total net input for this cell
setInputFunction(InputFunction) - Method in class org.neuroph.core.Neuron
  Sets input function
setInputNeurons(Vector<Neuron>) - Method in class org.neuroph.core.NeuralNetwork
  Sets reference to input neurons Vector
setIsCompeting(boolean) - Method in class org.neuroph.nnet.comp.CompetitiveNeuron
  Sets the flag to indicate that this neuron is in competing mode
setIterations(int, int) - Method in class org.neuroph.nnet.learning.KohonenLearning
setLabel(String) - Method in class org.neuroph.core.learning.TrainingElement
  Set training element label
setLabel(String) - Method in class org.neuroph.core.learning.TrainingSet
  Sets label for this training set
setLabel(Object, String) - Method in class org.neuroph.util.plugins.LabelsPlugin
  Sets label for the specified object
setLearningRate(double) - Method in class org.neuroph.core.learning.IterativeLearning
  Sets learning rate for this algorithm
setLearningRate(double) - Method in class org.neuroph.nnet.learning.KohonenLearning
setLearningRateChange(double) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
setLearningRule(LearningRule) - Method in class org.neuroph.core.NeuralNetwork
  Sets learning algorithm for this network
setLeftHigh(double) - Method in class org.neuroph.core.transfer.Trapezoid
  Sets left high point of trapezoid function
setLeftLow(double) - Method in class org.neuroph.core.transfer.Trapezoid
  Sets left low point of trapezoid function
setMaxCounter(int) - Method in class org.neuroph.samples.stockmarket.StockFileReader
setMaxCounter(int) - Method in class org.neuroph.samples.stockmarket.StockSocketReader
setMaxError(double) - Method in class org.neuroph.core.learning.SupervisedLearning
  Sets allowed network error, which indicates when to stopLearning training
setMaxIterations(int) - Method in class org.neuroph.core.learning.IterativeLearning
  Sets iteration limit for this learning algorithm
setMaxIterations(int) - Method in class org.neuroph.nnet.comp.CompetitiveLayer
  Sets max iterations for neurons to compete in this layer
setMaxLearningRate(double) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
setMaxMomentum(double) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
setMinErrorChange(double) - Method in class org.neuroph.core.learning.SupervisedLearning
  Sets min error change stopping criteria
setMinErrorChangeIterationsLimit(int) - Method in class org.neuroph.core.learning.SupervisedLearning
  Sets number of iterations for min error change stopping criteria
setMinLearningRate(double) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
setMinMomentum(double) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
setMomentum(double) - Method in class org.neuroph.nnet.learning.MomentumBackpropagation
  Sets the momentum factor
setMomentumChange(double) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
setNetworkType(NeuralNetworkType) - Method in class org.neuroph.core.NeuralNetwork
  Sets type for this network
setNeuralNetwork(NeuralNetwork) - Method in class org.neuroph.core.learning.LearningRule
  Sets neural network for this learning rule
setNeuron(int, Neuron) - Method in class org.neuroph.core.Layer
  Sets (replace) the neuron at specified position in layer
setNormalizer(double) - Method in class org.neuroph.samples.stockmarket.TrainingData
setOutput(double) - Method in class org.neuroph.core.Neuron
  Sets this neuron output
setOutputNeurons(Vector<Neuron>) - Method in class org.neuroph.core.NeuralNetwork
  Sets reference to output neurons Vector.
setParentLayer(Layer) - Method in class org.neuroph.core.Neuron
  Sets reference to parent layer for this neuron (layer in which the neuron is located)
setParentNetwork(NeuralNetwork) - Method in class org.neuroph.core.Layer
  Sets reference on parent network
setParentNetwork(NeuralNetwork) - Method in class org.neuroph.util.plugins.PluginBase
  Sets the parent network for this plugin
setPreviousValue(double) - Method in class org.neuroph.core.Weight
  Sets the previous weight value
setProperty(String, Object) - Method in class org.neuroph.util.NeuronProperties
setProperty(String, Object) - Method in class org.neuroph.util.Properties
setRightHigh(double) - Method in class org.neuroph.core.transfer.Trapezoid
  Sets right high point of trapezoid function
setRightLow(double) - Method in class org.neuroph.core.transfer.Trapezoid
  Sets right low point of trapezoid function
setSigma(double) - Method in class org.neuroph.core.transfer.Gaussian
  Sets the sigma parametar for this function
setSlope(double) - Method in class org.neuroph.core.transfer.Linear
  Sets the slope parametar for this function
setSlope(Double) - Method in class org.neuroph.core.transfer.Sigmoid
  Sets the slope parametar for this function
setSlope(double) - Method in class org.neuroph.core.transfer.Tanh
  Sets the slope parametar for this function
setThresh(double) - Method in class org.neuroph.nnet.comp.ThresholdNeuron
  Sets threshold value for this neuron
setTrainingSet(TrainingSet) - Method in class org.neuroph.core.learning.LearningRule
  Sets training set for this learning rule
setTrainingSet(TrainingSet) - Method in class org.neuroph.samples.stockmarket.TrainingData
setTransferFunction(TransferFunction) - Method in class org.neuroph.core.Neuron
  Sets transfer function
setTsleep(long) - Method in class org.neuroph.samples.stockmarket.StockSocketReader
setUseDynamicLearningRate(boolean) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
setUseDynamicMomentum(boolean) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
setValue(double) - Method in class org.neuroph.core.Weight
  Sets the weight value
setValuesRow(String[]) - Method in class org.neuroph.samples.stockmarket.StockFileReader
setValuesRow(String[]) - Method in class org.neuroph.samples.stockmarket.StockSocketReader
setValuesRow(String[]) - Method in class org.neuroph.samples.stockmarket.TrainingData
setXHigh(double) - Method in class org.neuroph.core.transfer.Ramp
  Sets threshold for the high output level
setXLow(double) - Method in class org.neuroph.core.transfer.Ramp
  Sets threshold for the low output level
setYHigh(double) - Method in class org.neuroph.core.transfer.Ramp
  Sets output value for the high output level
setYHigh(double) - Method in class org.neuroph.core.transfer.Step
  Set output value for the high output level
setYLow(double) - Method in class org.neuroph.core.transfer.Ramp
  Sets output value for the low output level
setYLow(double) - Method in class org.neuroph.core.transfer.Step
  Set output value for the low output level
Sgn - Class in org.neuroph.core.transfer
  Sgn neuron transfer function.
Sgn() - Constructor for class org.neuroph.core.transfer.Sgn
Sigmoid - Class in org.neuroph.core.transfer
  Sigmoid neuron transfer function.
Sigmoid() - Constructor for class org.neuroph.core.transfer.Sigmoid
  Creates an instance of Sigmoid neuron transfer function with default slope=1.
Sigmoid(double) - Constructor for class org.neuroph.core.transfer.Sigmoid
  Creates an instance of Sigmoid neuron transfer function with specified value for slope parametar.
Sigmoid(Properties) - Constructor for class org.neuroph.core.transfer.Sigmoid
  Creates an instance of Sigmoid neuron transfer function with the specified properties.
SigmoidDeltaRule - Class in org.neuroph.nnet.learning
  Delta rule learning algorithm for perceptrons with sigmoid (or any other diferentiable continuous) functions.
SigmoidDeltaRule() - Constructor for class org.neuroph.nnet.learning.SigmoidDeltaRule
  Creates new SigmoidDeltaRule
SigmoidDeltaRule(NeuralNetwork) - Constructor for class org.neuroph.nnet.learning.SigmoidDeltaRule
  Creates new SigmoidDeltaRule for the specified neural network
size() - Method in class org.neuroph.core.learning.TrainingSet
  Returns number of training elements in this training set set
Step - Class in org.neuroph.core.transfer
  Step neuron transfer function.
Step() - Constructor for class org.neuroph.core.transfer.Step
  Creates an instance of Step transfer function
Step(Properties) - Constructor for class org.neuroph.core.transfer.Step
  Creates an instance of Step transfer function with specified properties
StockFileReader - Class in org.neuroph.samples.stockmarket
  Provides method to reads stock data from the file.
StockFileReader() - Constructor for class org.neuroph.samples.stockmarket.StockFileReader
StockFileReader(int) - Constructor for class org.neuroph.samples.stockmarket.StockFileReader
StockSocketReader - Class in org.neuroph.samples.stockmarket
  Provides method to reads stock data from the socket.
StockSocketReader() - Constructor for class org.neuroph.samples.stockmarket.StockSocketReader
StockSocketReader(int) - Constructor for class org.neuroph.samples.stockmarket.StockSocketReader
StockTrainingSetImport - Class in org.neuroph.samples.stockmarket
  The part of simple stock market components, easy to use stock market interface for neural network.
StockTrainingSetImport() - Constructor for class org.neuroph.samples.stockmarket.StockTrainingSetImport
stopLearning() - Method in class org.neuroph.core.learning.LearningRule
  Stops learning
stopLearning() - Method in class org.neuroph.core.NeuralNetwork
  Stops learning
Sum - Class in org.neuroph.core.input
  Performs summing of all input vector elements.
Sum() - Constructor for class org.neuroph.core.input.Sum
SummingFunction - Class in org.neuroph.core.input
  Abstract base class for all summing functions, which perform some summing operation on weighted input vector and return scalar.
SummingFunction() - Constructor for class org.neuroph.core.input.SummingFunction
SummingFunctionType - Enum in org.neuroph.util
  Contains summing functions types and labels.
SumSqr - Class in org.neuroph.core.input
  Calculates squared sum of all input vector elements.
SumSqr() - Constructor for class org.neuroph.core.input.SumSqr
SupervisedHebbianLearning - Class in org.neuroph.nnet.learning
  Supervised hebbian learning rule.
SupervisedHebbianLearning() - Constructor for class org.neuroph.nnet.learning.SupervisedHebbianLearning
  Creates new instance of SupervisedHebbianLearning algorithm
SupervisedHebbianLearning(NeuralNetwork) - Constructor for class org.neuroph.nnet.learning.SupervisedHebbianLearning
  Creates new instance of SupervisedHebbianLearning algorithm for the specified neural network.
SupervisedHebbianNetwork - Class in org.neuroph.nnet
  Hebbian neural network with supervised Hebbian learning algorithm.
SupervisedHebbianNetwork(int, int) - Constructor for class org.neuroph.nnet.SupervisedHebbianNetwork
  Creates an instance of Supervised Hebbian Network net with specified number neurons in input and output layer
SupervisedHebbianNetwork(int, int, TransferFunctionType) - Constructor for class org.neuroph.nnet.SupervisedHebbianNetwork
  Creates an instance of Supervised Hebbian Network with specified number of neurons in input layer and output layer, and transfer function
SupervisedLearning - Class in org.neuroph.core.learning
  Base class for all supervised learning algorithms.
SupervisedLearning() - Constructor for class org.neuroph.core.learning.SupervisedLearning
  Creates new supervised learning rule
SupervisedLearning(NeuralNetwork) - Constructor for class org.neuroph.core.learning.SupervisedLearning
  Creates new supervised learning rule and sets the neural network to train
SupervisedTrainingElement - Class in org.neuroph.core.learning
  Represents training element for supervised learning algorithms.
SupervisedTrainingElement(Vector<Double>, Vector<Double>) - Constructor for class org.neuroph.core.learning.SupervisedTrainingElement
  Creates new training element with specified input and desired output vectors
SupervisedTrainingElement(String, String) - Constructor for class org.neuroph.core.learning.SupervisedTrainingElement
  Creates new training element with specified input and desired output vectors specifed as strings
SupervisedTrainingElement(double[], double[]) - Constructor for class org.neuroph.core.learning.SupervisedTrainingElement
  Creates new training element with specified input and desired output vectors

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