Package weka.classifiers.functions.neural

# Interface NeuralMethod

All Superinterfaces:
  `Serializable`

All Known Implementing Classes:
  `LinearUnit`, `SigmoidUnit`

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

Version:
  $Revision: 8034 $
Author:
  Malcolm Ware (mfw4@cs.waikato.ac.nz)

- ## Method Summary

  Modifier and Type
  Method
  Description
  `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 Details

  - ### 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.