C# Class Accord.Neuro.Learning.BackPropagationLearning

Back propagation learning algorithm.

The class implements back propagation learning algorithm, which is widely used for training multi-layer neural networks with continuous activation functions.

Sample usage (training network to calculate XOR function):

 // initialize input and output values double[][] input = new double[4][] { new double[] {0, 0}, new double[] {0, 1}, new double[] {1, 0}, new double[] {1, 1} }; double[][] output = new double[4][] { new double[] {0}, new double[] {1}, new double[] {1}, new double[] {0} }; // create neural network ActivationNetwork   network = new ActivationNetwork( SigmoidFunction( 2 ), 2, // two inputs in the network 2, // two neurons in the first layer 1 ); // one neuron in the second layer // create teacher BackPropagationLearning teacher = new BackPropagationLearning( network ); // loop while ( !needToStop ) { // run epoch of learning procedure double error = teacher.RunEpoch( input, output ); // check error value to see if we need to stop // ... }

Inheritance: ISupervisedLearning

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Public Methods

Method	Description
BackPropagationLearning ( ActivationNetwork network ) : System	Initializes a new instance of the BackPropagationLearning 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.

Private Methods

Method	Description
CalculateError ( double desiredOutput ) : double	Calculates error values for all neurons of the network.
CalculateUpdates ( double input ) : void	Calculate weights updates.
UpdateNetwork ( ) : void	Update network's weights.

Method Details

BackPropagationLearning() public method

Initializes a new instance of the BackPropagationLearning class.

public BackPropagationLearning ( 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