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## 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

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