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java.lang.Objectorg.encog.neural.pattern.RadialBasisPattern
public class RadialBasisPattern
A radial basis function (RBF) network uses several radial basis functions to provide a more dynamic hidden layer activation function than many other types of neural network. It consists of a input, output and hidden layer.
Constructor Summary | |
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RadialBasisPattern()
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Method Summary | |
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void |
addHiddenLayer(int count)
Add the hidden layer, this should be called once, as a RBF has a single hidden layer. |
void |
clear()
Clear out any hidden neurons. |
MLMethod |
generate()
Generate the RBF network. |
void |
setActivationFunction(ActivationFunction activation)
Set the activation function, this is an error. |
void |
setInputNeurons(int count)
Set the number of input neurons. |
void |
setOutputNeurons(int count)
Set the number of output neurons. |
void |
setRBF(RBFEnum type)
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Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public RadialBasisPattern()
Method Detail |
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public void addHiddenLayer(int count)
addHiddenLayer
in interface NeuralNetworkPattern
count
- The number of neurons in the hidden layer.public void clear()
clear
in interface NeuralNetworkPattern
public MLMethod generate()
generate
in interface NeuralNetworkPattern
public void setActivationFunction(ActivationFunction activation)
setActivationFunction
in interface NeuralNetworkPattern
activation
- The new activation function.public void setInputNeurons(int count)
setInputNeurons
in interface NeuralNetworkPattern
count
- The number of input neurons.public void setOutputNeurons(int count)
setOutputNeurons
in interface NeuralNetworkPattern
count
- The number of output neurons.public void setRBF(RBFEnum type)
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