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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
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