INeuralNet

All Known Implementing Classes:

AbstractNeuralNet, MSEOptimizablePUNeuralNetClassifier, MSEOptimizablePUNeuralNetRegressor, MSEOptimizableSigmNeuralNetClassifier, MSEOptimizableSigmNeuralNetRegressor, NeuralNetClassifier, NeuralNetRegressor
```
public interface INeuralNet
```
Represents a neural net

Since:

JDK1.5

Version:

0.1

Author:

Written by Pedro Antonio Gutierrez Penya, Aaron Ruiz Mora (University of Cordoba) 17/07/2007

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method and Description
`void`	`addHlayer(LinkedLayer layer)` Adds a new layer to the neural net
`INeuralNet`	`copy()` Returns a copy of the neural net
`boolean`	`equals(INeuralNet other)` Checks if this neural net is equal to another
`LinkedLayer`	`getHlayer(int index)` Returns a specific hidden layer of the neural net
`InputLayer`	`getInputLayer()` Returns the input layer of this neural net
`int`	`getNofhlayers()` Returns the current number of hidden layers of the neural net
`int`	`getNofhneurons()` Returns the number of hidden neurons of this neural net
`int`	`getNoflinks()` Returns the number of effective links of this neural net
`LinkedLayer`	`getOutputLayer()` Returns the output layer of this neural net
`int`	`hashCode()` Returns an integer number that identifies the neural net
`void`	`keepRelevantLinks(double significativeWeight)` Keep relevant links, that is, those links whose weight is higher than certain number
`boolean`	`linksEmpty()` Checks if this neural net is empty of links
`boolean`	`linksFull()` Checks if this neural net is full of links
`boolean`	`neuronsEmpty()` Checks if this neural net is empty of neurons
`boolean`	`neuronsFull()` Checks if this neural net is full of neurons
`void`	`setInputLayer(InputLayer inputLayer)` Sets the input layer of this neural net
`void`	`setOutputLayer(LinkedLayer outputLayer)` Sets the output layer of this neural net

- Method Detail
  - getNofhlayers
```
int getNofhlayers()
```
    Returns the current number of hidden layers of the neural net
    
    Returns:
    
    int Number of hidden layers
  - getInputLayer
```
InputLayer getInputLayer()
```
    Returns the input layer of this neural net
    
    Returns:
    
    InputLayer Input layer of the net
  - getHlayer
```
LinkedLayer getHlayer(int index)
```
    Returns a specific hidden layer of the neural net
    
    Parameters:
    
    index - Number of layer to return
    
    Returns:
    
    LinkedLayer Hidden layer
  - getOutputLayer
```
LinkedLayer getOutputLayer()
```
    Returns the output layer of this neural net
    
    Returns:
    
    LinkedLayer Output layer of the net
  - setInputLayer
```
void setInputLayer(InputLayer inputLayer)
```
    Sets the input layer of this neural net
    
    Parameters:
    
    inputLayer - New input layer of the net
  - addHlayer
```
void addHlayer(LinkedLayer layer)
```
    Adds a new layer to the neural net
    
    Parameters:
    
    layer - New hidden layer
  - setOutputLayer
```
void setOutputLayer(LinkedLayer outputLayer)
```
    Sets the output layer of this neural net
    
    Parameters:
    
    outputLayer - New output layer of the net
  - copy
```
INeuralNet copy()
```
    Returns a copy of the neural net
    
    Returns:
    
    INeuralNet Copy of the neural net
  - equals
```
boolean equals(INeuralNet other)
```
    Checks if this neural net is equal to another
    
    Parameters:
    
    other - Other neural net to compare
    
    Returns:
    
    true if both neural nets are equals
  - hashCode
```
int hashCode()
```
    Returns an integer number that identifies the neural net
    
    Overrides:
    
    hashCode in class java.lang.Object
    
    Returns:
    
    int Hashcode
  - neuronsFull
```
boolean neuronsFull()
```
    Checks if this neural net is full of neurons
    
    Returns:
    
    true if the neural net is full of neurons
  - neuronsEmpty
```
boolean neuronsEmpty()
```
    Checks if this neural net is empty of neurons
    
    Returns:
    
    true if the neural net is empty of neurons
  - linksFull
```
boolean linksFull()
```
    Checks if this neural net is full of links
    
    Returns:
    
    true if the neural net is full of links
  - linksEmpty
```
boolean linksEmpty()
```
    Checks if this neural net is empty of links
    
    Returns:
    
    true if the neural net is empty of links
  - getNofhneurons
```
int getNofhneurons()
```
    Returns the number of hidden neurons of this neural net
    
    Returns:
    
    int Number of hidden neurons
  - getNoflinks
```
int getNoflinks()
```
    Returns the number of effective links of this neural net
    
    Returns:
    
    int Number of effective links
  - keepRelevantLinks
```
void keepRelevantLinks(double significativeWeight)
```
    Keep relevant links, that is, those links whose weight is higher than certain number
    
    Parameters:
    
    significativeWeight - Significative weight

Interface INeuralNet

Method Summary

Method Detail

getNofhlayers

getInputLayer

getHlayer

getOutputLayer

setInputLayer

addHlayer

setOutputLayer

copy

equals

hashCode

neuronsFull

neuronsEmpty

linksFull

linksEmpty

getNofhneurons

getNoflinks

keepRelevantLinks