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## org.encog.neural.networks.training.cross
Class CrossTraining

    java.lang.Object
      org.encog.ml.train.BasicTraining
          org.encog.neural.networks.training.cross.CrossTraining

All Implemented Interfaces:
  MLTrain

Direct Known Subclasses:
  CrossValidationKFold

    public abstract class CrossTraining

extends BasicTraining

Base class for cross training trainers. Must use a folded dataset.

Constructor Summary
`CrossTraining(MLMethod network, FoldedDataSet training)` Construct a cross trainer.

Method Summary
`FoldedDataSet` | `getFolded()`
`MLMethod` | `getMethod()` Get the current best machine learning method from the training.

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`

Methods inherited from interface org.encog.ml.train.MLTrain
`canContinue, iteration, pause, resume`

Constructor Detail

### CrossTraining

    public CrossTraining(MLMethod network,
                         FoldedDataSet training)

  Construct a cross trainer.

  Parameters:
    `network` - The network.
    `training` - The training data.

Method Detail

### getFolded

    public FoldedDataSet getFolded()

  Returns:
    The folded training data.

### getMethod

    public MLMethod getMethod()

  Get the current best machine learning method from the training.

  Returns:
    The best machine learningm method.

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