org.encog.neural.pattern
public class SVMPattern extends Object implements NeuralNetworkPattern
Constructor and Description |
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SVMPattern() |
Modifier and Type | Method and Description |
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void |
addHiddenLayer(int count)
Unused, a BAM has no hidden layers.
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void |
clear()
Clear any settings on the pattern.
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MLMethod |
generate()
Generate the specified neural network.
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int |
getInputNeurons() |
int |
getOutputNeurons() |
boolean |
isRegression() |
void |
setActivationFunction(ActivationFunction activation)
Not used, the BAM uses a bipoloar activation function.
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void |
setInputNeurons(int count)
Set the number of input neurons.
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void |
setKernelType(KernelType kernelType)
Set the kernel type.
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void |
setOutputNeurons(int count)
Set the number of output neurons.
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void |
setRegression(boolean regression)
Set if regression is used.
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void |
setSVMType(SVMType svmType)
Set the SVM type.
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public void addHiddenLayer(int count)
addHiddenLayer
in interface NeuralNetworkPattern
count
- Not used.public void clear()
clear
in interface NeuralNetworkPattern
public MLMethod generate()
NeuralNetworkPattern
generate
in interface NeuralNetworkPattern
public int getInputNeurons()
public int getOutputNeurons()
public boolean isRegression()
public void setActivationFunction(ActivationFunction activation)
setActivationFunction
in interface NeuralNetworkPattern
activation
- Not used.public void setInputNeurons(int count)
setInputNeurons
in interface NeuralNetworkPattern
count
- The number of input neurons.public void setKernelType(KernelType kernelType)
kernelType
- The kernel type.public void setOutputNeurons(int count)
setOutputNeurons
in interface NeuralNetworkPattern
count
- The output neuron count.public void setRegression(boolean regression)
regression
- True if regression is used.public void setSVMType(SVMType svmType)
svmType
- The SVM type.Copyright © 2014. All Rights Reserved.