Class Summary |
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. |