C# Class Accord.Neuro.Learning.DeltaRuleLearning

Delta rule learning algorithm.

This learning algorithm is used to train one layer neural network of Activation Neurons with continuous activation function, see SigmoidFunction for example.

See information about delta rule learning algorithm.

Inheritance: ISupervisedLearning
Datei anzeigen Open project: accord-net/framework Class Usage Examples

Public Methods

Method Description
DeltaRuleLearning ( ActivationNetwork network ) : System

Initializes a new instance of the DeltaRuleLearning class.

Run ( double input, double output ) : double

Runs learning iteration.

Runs one learning iteration and updates neuron's weights.

RunEpoch ( double input, double output ) : double

Runs learning epoch.

The method runs one learning epoch, by calling Run method for each vector provided in the input array.

Method Details

DeltaRuleLearning() public method

Initializes a new instance of the DeltaRuleLearning class.
Invalid nuaral network. It should have one layer only.
public DeltaRuleLearning ( ActivationNetwork network ) : System
network ActivationNetwork Network to teach.
return System

Run() public method

Runs learning iteration.

Runs one learning iteration and updates neuron's weights.

public Run ( double input, double output ) : double
input double Input vector.
output double Desired output vector.
return double

RunEpoch() public method

Runs learning epoch.

The method runs one learning epoch, by calling Run method for each vector provided in the input array.

public RunEpoch ( double input, double output ) : double
input double Array of input vectors.
output double Array of output vectors.
return double