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## weka.classifiers.functions.neural
Interface NeuralMethod

All Superinterfaces:
  java.io.Serializable

All Known Implementing Classes:
  LinearUnit, SigmoidUnit

    public interface NeuralMethod

extends java.io.Serializable

This is an interface used to create classes that can be used by the neuralnode to perform all it's computations.

Version:
  $Revision: 1.6 $
Author:
  Malcolm Ware (mfw4@cs.waikato.ac.nz)

Method Summary
`double` | `errorValue(NeuralNode node)` This function calculates what the error value should be.
`double` | `outputValue(NeuralNode node)` This function calculates what the output value should be.
`void` | `updateWeights(NeuralNode node, double learn, double momentum)` This function will calculate what the change in weights should be and also update them.

Method Detail

### outputValue

    double outputValue(NeuralNode node)

  This function calculates what the output value should be.

  Parameters:
    `node` - The node to calculate the value for.
  Returns:
    The value.

### errorValue

    double errorValue(NeuralNode node)

  This function calculates what the error value should be.

  Parameters:
    `node` - The node to calculate the error for.
  Returns:
    The error.

### updateWeights

    void updateWeights(NeuralNode node,
                       double learn,
                       double momentum)

  This function will calculate what the change in weights should be and also update them.

  Parameters:
    `node` - The node to update the weights for.
    `learn` - The learning rate to use.
    `momentum` - The momentum to use.

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