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1. Processing Examples
An example run can be made for each processing option in
this package, using the data files in directory
\neuron\batchm\dat. These processing examples are run as follows.
a. Go to the subdirectory \neuron\batchm\dat
b. Start up Nuron
c. Go to the option you are interested in. However, under
"Multilayer Perceptron Processing", you cannot "Analyze
a Trained MLP" until you have designed one.
d. Choose batch processing. The dos editor will edit a parameter
file, which has responses to programs requests
e. Exit the Dos editor. The program will now run using responses in
the parameter file.
f. Choose the "Examine Program Output" option, if you like.
g. For further details on the examples, see the help files for
the option you are interested in.
2. Designing a MLP Neural Net for Your Own Data
a. Obtain an ascii data file and put it in the proper format. File
Gls is a good example. Figure out how many inputs or features
your data has and how many outputs you have.
b. Decide how many hidden layers (1 or 2) you want and how many
hidden units (up to 40 per layer) you want. One way to do this
is to "Estimate Network Structure" under the "Data Format and
Pre-Processing" option. Create a network structure file by
editing a copy of Gls.top or during the manual run of the
backpropagation program or fast training program.
c. Decide whether you want to use backpropagation training or fast
training. Fast training is recommended.
d. Go to the "Batch Processing" option under "Fast Training" or
"Backpropagation Training", which are under the "Multilayer
Perceptron Processing" menu.
e. Alter the keyboard response file, following the choices you
have made, and exit the EDIT program. The training program will
now run.
f. Choose the "Examine Program Output" option if you like.