org.encog.neural.cpn.training
Class TrainOutstar

java.lang.Object
  extended by org.encog.ml.train.BasicTraining
      extended by 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 boolean canContinue()

Specified by:
canContinue in interface MLTrain
Returns:
True if the training can be paused, and later continued.

getLearningRate

public double getLearningRate()

Specified by:
getLearningRate in interface LearningRate
Returns:
The learning rate.

getMethod

public 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 void iteration()
Perform one iteration of training.

Specified by:
iteration in interface MLTrain

pause

public TrainingContinuation pause()
Pause the training to continue later.

Specified by:
pause in interface MLTrain
Returns:
A training continuation object.

resume

public void resume(TrainingContinuation state)
Resume training.

Specified by:
resume in interface MLTrain
Parameters:
state - The training continuation object to use to continue.

setLearningRate

public void setLearningRate(double rate)
Set the learning rate.

Specified by:
setLearningRate in interface LearningRate
Parameters:
rate - The new learning rate


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