Class | Description |
---|---|
BatchModeExtender |
This class implements the offline learning, that is, batch mode.
|
DeltaRuleExtender |
This abstract class describes the methods needed for a delta rule extender,
that is, a class that computes / changes the delta (update weight) value
according to some algorithm.
|
GradientExtender |
This abstract class describes the methods needed for a gradient extender,
that is, a class that computes / changes the gradient value according to
some algorithm.
|
LearnerExtender |
This abstract class describes the methods that any learner extender must
provide.
|
MomentumExtender |
This extender implements the momentum term.
|
OnlineModeExtender |
This is the default weight updater (online).
|
RpropExtender |
This class changes the delta value in such a way that it implements the
RPROP algorithm.
|
SimulatedAnnealingExtender |
Simulated annealing (SA) refers to the process in which random or thermal
noise in a system is systematically decreased over time so as to enhance
the system's response.
|
UpdateWeightExtender |
This abstract class describes the methods needed for a update weight extender, that is,
a class that updates weights (storing) according to some algorithm (e.g.
|
WeightDecayExtender |
Weight decay adds a penalty term to the error function.
|
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