org.encog.neural.networks.training.propagation
Class Propagation

java.lang.Object
  org.encog.neural.networks.training.BasicTraining
      org.encog.neural.networks.training.propagation.Propagation

All Implemented Interfaces:

Train

Direct Known Subclasses:

Backpropagation, ManhattanPropagation, ResilientPropagation, ScaledConjugateGradient

public abstract class Propagation
extends BasicTraining

Implements basic functionality that is needed by each of the propagation methods. The specifics of each of the propagation methods is implemented inside of the PropagationMethod interface implementors.

Author:

jheaton

Constructor Summary

Propagation(BasicNetwork network, NeuralDataSet training)
Construct a propagation object.

Method Summary

boolean	canContinue()
BasicNetwork	getNetwork() Get the current best network from the training.
int	getNumThreads()
boolean	isValidResume(TrainingContinuation state) Determine if this specified training continuation object is valid for this training method.
void	iteration() Perform one training iteration.
TrainingContinuation	pause() Pause the training to continue later.
abstract void	performIteration(CalculateGradient prop, double[] weights) Perform an iteration.
void	resume(TrainingContinuation state) Resume training.
void	setNumThreads(int numThreads) Set the number of threads.

Methods inherited from class org.encog.neural.networks.training.BasicTraining

addStrategy, finishTraining, getError, getStrategies, getTraining, postIteration, preIteration, setError, setTraining

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Propagation

public Propagation(BasicNetwork network,
                   NeuralDataSet training)

Construct a propagation object.

Parameters:

network - The network.

training - The training set.

Method Detail

canContinue

public boolean canContinue()

Returns:

True if this training can be continued.

getNetwork

public BasicNetwork getNetwork()

Description copied from interface: Train

Get the current best network from the training.

Returns:

The network.

getNumThreads

public int getNumThreads()

Returns:

The number of threads.

isValidResume

public boolean isValidResume(TrainingContinuation state)

Determine if this specified training continuation object is valid for this training method.

Parameters:

state - The training continuation object to check.

Returns:

True if the continuation object is valid.

iteration

public void iteration()

Perform one training iteration.

pause

public TrainingContinuation pause()

Pause the training to continue later.

Returns:

A training continuation object.

performIteration

public abstract void performIteration(CalculateGradient prop,
                                      double[] weights)

Perform an iteration. This is implemented for each of the propagation method types.

Parameters:

prop - The gradients.

weights - The weights.

resume

public void resume(TrainingContinuation state)

Resume training.

Parameters:

state - The training continuation object to use to continue.

setNumThreads

public void setNumThreads(int numThreads)

Set the number of threads.

Parameters:

numThreads - The number of threads.