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

    java.lang.Object
      org.encog.neural.networks.training.cross.NetworkFold

    public class NetworkFold

extends Object

The network for one fold of a cross validation.

Constructor Summary
`NetworkFold(FlatNetwork flat)` Construct a fold from the specified flat network.

Method Summary
`void` | `copyFromNetwork(FlatNetwork source)` Copy the weights and output from the network.
`void` | `copyToNetwork(FlatNetwork target)` Copy weights and output to the network.
`double[]` | `getOutput()`
`double[]` | `getWeights()`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### NetworkFold

    public NetworkFold(FlatNetwork flat)

  Construct a fold from the specified flat network.

  Parameters:
    `flat` - THe flat network.

Method Detail

### copyToNetwork

    public final void copyToNetwork(FlatNetwork target)

  Copy weights and output to the network.

  Parameters:
    `target` - The network to copy to.

### copyFromNetwork

    public final void copyFromNetwork(FlatNetwork source)

  Copy the weights and output from the network.

  Parameters:
    `source` - The network to copy from.

### getWeights

    public final double[] getWeights()

  Returns:
    The network weights.

### getOutput

    public final double[] getOutput()

  Returns:
    The network output.

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