C# Class Encog.ML.Train.Strategy.ResetStrategy

The reset strategy will reset the weights if the neural network fails to fall below a specified error by a specified number of cycles. This can be useful to throw out initially "bad/hard" random initializations of the weight matrix.

Inheritance: IStrategy

Show file Open project: encog/encog-silverlight-core

Public Methods

Method	Description
Init ( IMLTrain train ) : void	Initialize this strategy.
PostIteration ( ) : void	Called just after a training iteration.
PreIteration ( ) : void	Called just before a training iteration.
ResetStrategy ( double required, int cycles ) : Encog.Neural.Networks.Training	Construct a reset strategy. The error rate must fall below the required rate in the specified number of cycles, or the neural network will be reset to random weights and bias values.

Method Details

Init() public method

Initialize this strategy.

public Init ( IMLTrain train ) : void
train	IMLTrain	The training algorithm.
return	void

PostIteration() public method

Called just after a training iteration.

public PostIteration ( ) : void
return	void

PreIteration() public method

Called just before a training iteration.

public PreIteration ( ) : void
return	void

ResetStrategy() public method

Construct a reset strategy. The error rate must fall below the required rate in the specified number of cycles, or the neural network will be reset to random weights and bias values.

public ResetStrategy ( double required, int cycles ) : Encog.Neural.Networks.Training
required	double	The required error rate.
cycles	int	The number of cycles to reach that rate.
return	Encog.Neural.Networks.Training