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java.lang.Object | +--weka.classifiers.functions.neural.NeuralConnection | +--weka.classifiers.functions.neural.NeuralNode
This class is used to represent a node in the neuralnet.
Field Summary |
Fields inherited from class weka.classifiers.functions.neural.NeuralConnection |
CONNECTED, INPUT, OUTPUT, PURE_INPUT, PURE_OUTPUT, UNCONNECTED |
Constructor Summary | |
NeuralNode(java.lang.String id,
java.util.Random r,
NeuralMethod m)
|
Method Summary | |
double |
errorValue(boolean calculate)
Call this to get the error value of this unit. |
double[] |
getChangeInWeights()
call this function to get the chnage in weights array. |
NeuralMethod |
getMethod()
|
double[] |
getWeights()
call this function to get the weights array. |
double |
outputValue(boolean calculate)
Call this to get the output value of this unit. |
void |
removeAllInputs()
This function will remove all the inputs to this unit. |
void |
reset()
Call this to reset the value and error for this unit, ready for the next run. |
void |
setMethod(NeuralMethod m)
Set how this node should operate (note that the neural method has no internal state, so the same object can be used by any number of nodes. |
void |
updateWeights(double l,
double m)
Call this function to update the weight values at this unit. |
double |
weightValue(int n)
Call this to get the weight value on a particular connection. |
Methods inherited from class weka.classifiers.functions.neural.NeuralConnection |
connect, disconnect, drawHighlight, drawInputLines, drawNode, drawOutputLines, getId, getInputNums, getInputs, getNumInputs, getNumOutputs, getOutputNums, getOutputs, getType, getX, getY, onUnit, removeAllOutputs, setType, setX, setY |
Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
public NeuralNode(java.lang.String id, java.util.Random r, NeuralMethod m)
id
- The string name for this node (used to id this node).r
- A random number generator used to generate initial weights.m
- The methods this node should use to update.Method Detail |
public void setMethod(NeuralMethod m)
m
- The new method.public NeuralMethod getMethod()
public double outputValue(boolean calculate)
outputValue
in class NeuralConnection
calculate
- True if the value should be calculated if it hasn't been
already.
public double errorValue(boolean calculate)
errorValue
in class NeuralConnection
calculate
- True if the value should be calculated if it hasn't been
already.
public void reset()
reset
in class NeuralConnection
public double weightValue(int n)
weightValue
in class NeuralConnection
n
- The connection number to get the weight for, -1 if The threshold
weight should be returned.
public double[] getWeights()
public double[] getChangeInWeights()
public void updateWeights(double l, double m)
updateWeights
in class NeuralConnection
l
- The learning rate to use.m
- The momentum to use.public void removeAllInputs()
removeAllInputs
in class NeuralConnection
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Copyright (c) 2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London