This class is a command line test case (it has a main() method)
that creates a fuzzy ruleset, a fuzzy ruleset listener, wires the
two together, and then processes the rules.
set the internal config for either
NNTRAIN = training from an external data file
NNTEST = testing (with network locked) from an external data file
or NNRUN = running (with network locked) from data placed in the input buffer
set the internal config for either
NNTRAIN = training from an external data file
NNTEST = testing (with network locked) from an external data file
or NNRUN = running (with network locked) from data placed in the input buffer
set the internal config for either
NNTRAIN = training from an external data file
NNTEST = testing (with network locked) from an external data file
or NNRUN = running (with network locked) from data placed in the input buffer
set the internal config for either
NNTRAIN = training from an external data file
NNTEST = testing (with network locked) from an external data file
or NNRUN = running (with network locked) from data placed in the input buffer
Set the mutationRate, used when a mutate operator is selected
this value is used to determine whether each bit is mutated or not
mutation can be to any other value in the vocabulary
Set the back propagation network architecture
The architecture string is a sequence of space-delimited integers
as follows: numInput numHid1 numHid2 numHid3 numOutput feedbackType
Note if feedbackType is not specified, it will be set to 0
Set the back propagation network architecture
The architecture string is a sequence of space-delimited integers
as follows: numInput numHid1 numHid2 numHid3 numOutput feedbackType
Note if feedbackType is not specified, it will be set to 0
Set the back propagation network architecture
The architecture string is a sequence of space-delimited integers
as follows: numInput numHid1 numHid2 numHid3 numOutput feedbackType
Note if feedbackType is not specified, it will be set to 0
Set a hashtable of operators and their fitness values
These values are used to select operators for application during reproduction
Fitness values should sum to 100
start automatically training the model from the external data
this method is called from the customizer Start button
should only be called when agent is already in TRAIN state
start automatically training the model from the external data
this method is called from the customizer Start button
should only be called when agent is already in TRAIN state