C# Class AForge.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

Show file Open project: holisticware-admin/MonoVersal.AForgeNET 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