C# Class Encog.Neural.SOM.Training.Neighborhood.BasicTrainSOM

Inheritance: BasicTraining, ILearningRate

Public Methods

Method	Description
AutoDecay ( ) : void	Should be called each iteration if autodecay is desired.
BasicTrainSOM ( SOMNetwork network, double learningRate, IMLDataSet training, INeighborhoodFunction neighborhood ) : System	Create an instance of competitive training.
Decay ( double d ) : void	Called to decay the learning rate and radius by the specified amount.
Decay ( double decayRate, double decayRadius ) : void	Decay the learning rate and radius by the specified amount.
Iteration ( ) : void	Perform one training iteration.
Pause ( ) : TrainingContinuation
Resume ( TrainingContinuation state ) : void
SetAutoDecay ( int plannedIterations, double startRate, double endRate, double startRadius, double endRadius ) : void	Setup autodecay. This will decrease the radius and learning rate from the start values to the end values.
SetParams ( double rate, double radius ) : void	Set the learning rate and radius.
ToString ( ) : String
TrainPattern ( IMLData pattern ) : void	Train the specified pattern. Find a winning neuron and adjust all neurons according to the neighborhood function.

Method	Description
ApplyCorrection ( ) : void	Loop over the synapses to be trained and apply any corrections that were determined by this training iteration.
CopyInputPattern ( Matrix matrix, int outputNeuron, IMLData input ) : void	Copy the specified input pattern to the weight matrix. This causes an output neuron to learn this pattern "exactly". This is useful when a winner is to be forced.
DetermineNewWeight ( double weight, double input, int currentNeuron, int bmu ) : double	Determine the weight adjustment for a single neuron during a training iteration.
ForceWinners ( Matrix matrix, int won, IMLData leastRepresented ) : bool	Force any neurons that did not win to off-load patterns from overworked neurons.
Train ( int bmu, Matrix matrix, IMLData input ) : void	Train for the specified synapse and BMU.
TrainPattern ( Matrix matrix, IMLData input, int current, int bmu ) : void	Train for the specified pattern.

Should be called each iteration if autodecay is desired.

public AutoDecay ( ) : void
return	void

Create an instance of competitive training.

public BasicTrainSOM ( SOMNetwork network, double learningRate, IMLDataSet training, INeighborhoodFunction neighborhood ) : System
network	Encog.Neural.SOM.SOMNetwork	The network to train.
learningRate	double	The learning rate, how much to apply per iteration.
training	IMLDataSet	The training set (unsupervised).
neighborhood	INeighborhoodFunction	The neighborhood function to use.
return	System

Called to decay the learning rate and radius by the specified amount.

Decay the learning rate and radius by the specified amount.

public Decay ( double decayRate, double decayRadius ) : void
decayRate	double	The percent to decay the learning rate by.
decayRadius	double	The percent to decay the radius by.
return	void

Perform one training iteration.

public final Iteration ( ) : void
return	void

public final Pause ( ) : TrainingContinuation
return	Encog.Neural.Networks.Training.Propagation.TrainingContinuation

public Resume ( TrainingContinuation state ) : void
state	Encog.Neural.Networks.Training.Propagation.TrainingContinuation
return	void

Setup autodecay. This will decrease the radius and learning rate from the start values to the end values.

public SetAutoDecay ( int plannedIterations, double startRate, double endRate, double startRadius, double endRadius ) : void
plannedIterations	int
startRate	double	The starting learning rate.
endRate	double	The ending learning rate.
startRadius	double	The starting radius.
endRadius	double	The ending radius.
return	void

Set the learning rate and radius.

public SetParams ( double rate, double radius ) : void
rate	double	The new learning rate.
radius	double	The new radius.
return	void

public final ToString ( ) : String
return	String

Train the specified pattern. Find a winning neuron and adjust all neurons according to the neighborhood function.

public TrainPattern ( IMLData pattern ) : void
pattern	IMLData	The pattern to train.
return	void