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java.lang.Object | +--com.huguesjohnson.jail.neuralNetwork.Layer | +--com.huguesjohnson.jail.neuralNetwork.BackPropagationLayer
class BackPropagationLayer
Constructor Summary | |
BackPropagationLayer()
default constructor |
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BackPropagationLayer(int layerSize,
int inputSize,
double punishRate,
double rewardRate,
double errorThreshold,
double minWeight,
double maxWeight)
constructor |
Method Summary | |
void |
computeOutput()
computes the output for the layer |
void |
runComplete()
method invoked when run is complete |
void |
train()
move actual output closer to desired output by default find neuron with greatest error and adjust it |
Methods inherited from class com.huguesjohnson.jail.neuralNetwork.Layer |
adjustTrainingRate, computeError, getDesiredOutput, getDoneTraining, getError, getNeuron, getOutput, getOutput, getSize, initOutput, insertNeuron, insertNeuron, removeNeuron, run, setDesiredOutput, setDoneTraining, setInput, setNeuron, setOutput, start, stop, toString |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
public BackPropagationLayer()
public BackPropagationLayer(int layerSize, int inputSize, double punishRate, double rewardRate, double errorThreshold, double minWeight, double maxWeight)
layerSize
- the number of neurons in the layerinputSize
- the number of inputs to the layerpunishRate
- the punish rate for every neuron in the layerrewardRate
- the reward rate for every neuron in the layererrorThreshold
- the error threshold for every neuron in the layerminWeight
- minimum weight on a neuron linkmaxWeight
- maximum weight on a neuron linkMethod Detail |
public void runComplete()
runComplete
in class Layer
public void train()
train
in class Layer
public void computeOutput()
computeOutput
in class Layer
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