| Modifier and Type | Class and Description |
|---|---|
class |
BasicNetwork
This class implements a neural network.
|
| Modifier and Type | Field and Description |
|---|---|
protected ContainsFlat |
Propagation.network
The network to train.
|
| Constructor and Description |
|---|
Propagation(ContainsFlat network,
MLDataSet training)
Construct a propagation object.
|
| Constructor and Description |
|---|
Backpropagation(ContainsFlat network,
MLDataSet training)
Create a class to train using backpropagation.
|
Backpropagation(ContainsFlat network,
MLDataSet training,
double theLearnRate,
double theMomentum) |
| Constructor and Description |
|---|
ManhattanPropagation(ContainsFlat network,
MLDataSet training,
double theLearnRate)
Construct a Manhattan propagation training object.
|
| Constructor and Description |
|---|
QuickPropagation(ContainsFlat network,
MLDataSet training)
Construct a QPROP trainer for flat networks.
|
QuickPropagation(ContainsFlat network,
MLDataSet training,
double theLearningRate)
Construct a QPROP trainer for flat networks.
|
| Constructor and Description |
|---|
ResilientPropagation(ContainsFlat network,
MLDataSet training)
Construct an RPROP trainer, allows an OpenCL device to be specified.
|
ResilientPropagation(ContainsFlat network,
MLDataSet training,
double initialUpdate,
double maxStep)
Construct a resilient training object, allow the training parameters to
be specified.
|
| Constructor and Description |
|---|
ScaledConjugateGradient(ContainsFlat network,
MLDataSet training)
Construct a training class.
|
| Modifier and Type | Class and Description |
|---|---|
class |
RBFNetwork
RBF neural network.
|
| Modifier and Type | Method and Description |
|---|---|
static void |
EncogValidate.validateNetworkForTraining(ContainsFlat network,
MLDataSet training)
Validate a network for training.
|
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