Neuroph
A B C D E F G H I K L M N O P R S T U V W X

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
setE(Double) - Method in class org.neuroph.nnet.learning.StepDeltaRule
Sets the e parametar
setError(double) - Method in class org.neuroph.core.Neuron
Sets error for this neuron.
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
 
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
setMaxError(Double) - Method in class org.neuroph.core.learning.SupervisedLearning
Sets allowed network error, which indicates when to stopLearning training
setMaxIterations(Integer) - 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
setMomentum(double) - Method in class org.neuroph.nnet.learning.MomentumBackpropagation
Sets the momentum factor
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
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, Double) - Method in class org.neuroph.util.NeuronProperties
 
setProperty(String, TransferFunctionType) - Method in class org.neuroph.util.NeuronProperties
 
setProperty(String, WeightsFunctionType) - Method in class org.neuroph.util.NeuronProperties
 
setProperty(String, SummingFunctionType) - Method in class org.neuroph.util.NeuronProperties
 
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
setTransferFunction(TransferFunction) - Method in class org.neuroph.core.Neuron
Sets transfer function
setValue(double) - Method in class org.neuroph.core.Weight
Sets the weight value
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 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
StepDeltaRule - Class in org.neuroph.nnet.learning
Delta rule learning algorithm for perceptrons with step functions.
StepDeltaRule() - Constructor for class org.neuroph.nnet.learning.StepDeltaRule
Creates new StepDeltaRule learning
StepDeltaRule(NeuralNetwork) - Constructor for class org.neuroph.nnet.learning.StepDeltaRule
Creates new StepDeltaRule learning for the specified neural network
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

Neuroph
A B C D E F G H I K L M N O P R S T U V W X