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java.lang.Objectorg.joone.engine.Layer
org.joone.engine.SimpleLayer
org.joone.engine.LinearLayer
public class LinearLayer
The output of a linear layer neuron is the sum of the weighted input values, scaled by the beta parameter. No transfer function is applied to limit the output value
Field Summary |
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Fields inherited from class org.joone.engine.Layer |
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bias, gradientInps, gradientOuts, inps, inputPatternListeners, learnable, learning, m_batch, monitor, myLearner, outputPatternListeners, outs, running, step, STOP_FLAG |
Constructor Summary | |
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LinearLayer()
The constructor |
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LinearLayer(java.lang.String ElemName)
The constructor |
Method Summary | |
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void |
backward(double[] pattern)
Reverse transfer function of the component. |
void |
forward(double[] pattern)
Transfer function to recall a result on a trained net |
double |
getBeta()
Returns the value of the beta parameter |
java.util.Collection |
Inspections()
It doesn't make sense to return biases for this layer |
void |
setBeta(double newBeta)
Sets the beta value |
Methods inherited from class org.joone.engine.SimpleLayer |
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getLearningRate, getLrate, getMomentum, setDimensions, setLrate, setMomentum, setMonitor |
Methods inherited from class java.lang.Object |
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clone, equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public LinearLayer()
public LinearLayer(java.lang.String ElemName)
ElemName
- The name of the LayerMethod Detail |
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public void backward(double[] pattern)
Layer
backward
in class SimpleLayer
pattern
- input pattern on which to apply the transfer functionpublic void forward(double[] pattern)
Layer
forward
in class Layer
pattern
- input pattern to which to apply the rtransfer functionpublic double getBeta()
public void setBeta(double newBeta)
newBeta
- doublepublic java.util.Collection Inspections()
Inspections
in interface Inspectable
Inspections
in class Layer
org.joone.Inspection
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