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Uses of Train in org.encog.neural.networks.training.propagation |
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Classes in org.encog.neural.networks.training.propagation that implement Train | |
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Propagation
Implements basic functionality that is needed by each of the propagation methods. |
Uses of Train in org.encog.neural.networks.training.propagation.back |
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Classes in org.encog.neural.networks.training.propagation.back that implement Train | |
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class |
Backpropagation
This class implements a backpropagation training algorithm for feed forward neural networks. |
Uses of Train in org.encog.neural.networks.training.propagation.manhattan |
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Classes in org.encog.neural.networks.training.propagation.manhattan that implement Train | |
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class |
ManhattanPropagation
One problem that the backpropagation technique has is that the magnitude of the partial derivative may be calculated too large or too small. |
Uses of Train in org.encog.neural.networks.training.propagation.quick |
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Classes in org.encog.neural.networks.training.propagation.quick that implement Train | |
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class |
QuickPropagation
QPROP is an efficient training method that is based on Newton's Method. |
Uses of Train in org.encog.neural.networks.training.propagation.resilient |
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Classes in org.encog.neural.networks.training.propagation.resilient that implement Train | |
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class |
ResilientPropagation
One problem with the backpropagation algorithm is that the magnitude of the partial derivative is usually too large or too small. |
Uses of Train in org.encog.neural.networks.training.propagation.scg |
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Classes in org.encog.neural.networks.training.propagation.scg that implement Train | |
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class |
ScaledConjugateGradient
This is a training class that makes use of scaled conjugate gradient methods. |
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