org.encog.neural.cpn.training
Class TrainOutstar

java.lang.Object
  org.encog.ml.train.BasicTraining
      org.encog.neural.cpn.training.TrainOutstar

All Implemented Interfaces:

MLTrain, LearningRate

public class TrainOutstar
extends BasicTraining
implements LearningRate

Used for Instar training of a CPN neural network. A CPN network is a hybrid supervised/unsupervised network. The Outstar training handles the supervised portion of the training.

Constructor Summary

TrainOutstar(CPN theNetwork, MLDataSet theTraining, double theLearningRate)
Construct the outstar trainer.

Method Summary

boolean	canContinue()
double	getLearningRate()
MLMethod	getMethod() Get the current best machine learning method from the training.
void	iteration() Perform one iteration of training.
TrainingContinuation	pause() Pause the training to continue later.
void	resume(TrainingContinuation state) Resume training.
void	setLearningRate(double rate) Set the learning rate.

Methods inherited from class org.encog.ml.train.BasicTraining

addStrategy, finishTraining, getError, getImplementationType, getIteration, getStrategies, getTraining, isTrainingDone, iteration, postIteration, preIteration, setError, setIteration, setTraining

Methods inherited from class java.lang.Object

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

Constructor Detail

TrainOutstar

public TrainOutstar(CPN theNetwork,
                    MLDataSet theTraining,
                    double theLearningRate)

Construct the outstar trainer.

Parameters:

theNetwork - The network to train.

theTraining - The training data, must provide ideal outputs.

theLearningRate - The learning rate.

Method Detail

canContinue

public final boolean canContinue()

Specified by:

canContinue in interface MLTrain

Returns:

True if the training can be paused, and later continued.

getLearningRate

public final double getLearningRate()

Specified by:

getLearningRate in interface LearningRate

Returns:

The learning rate.

getMethod

public final MLMethod getMethod()

Get the current best machine learning method from the training.

Specified by:

getMethod in interface MLTrain

Returns:

The best machine learningm method.

iteration

public final void iteration()

Perform one iteration of training.

Specified by:

iteration in interface MLTrain

pause

public final TrainingContinuation pause()

Pause the training to continue later.

Specified by:

pause in interface MLTrain

Returns:

A training continuation object.

resume

public final void resume(TrainingContinuation state)

Resume training.

Specified by:

resume in interface MLTrain

Parameters:

state - The training continuation object to use to continue.

setLearningRate

public final void setLearningRate(double rate)

Set the learning rate.

Specified by:

setLearningRate in interface LearningRate

Parameters:

rate - The new learning rate