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1993-01-04
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1. Functions of the Network Structure Estimation Program
a. Reads a training data file
b. Requests a minimum acceptable training error
from the user,
c. Requests a maximum number of iterations from the user.
A typical number is 10.
d. Estimates the required network structure for an MLP to attain
the desired classification error percentage
e. Notifies user if the network will generalize or memorize
2. Example Run of the Network Structure Estimation Program
a. Go to the "Batch Processing" option and press <ret>
b. Observe the parameter file with commented keyboard responses;
Gls ! input training data filename
4 ! number of inputs per pattern
1 ! number of outputs per pattern
.001 ! maximum acceptable mean-square training error
8 ! maximum allowable number of iterations
Here, we will estimate the required size of an MLP for
predicting chaotic time series created by the Mackey-Glass
delay-difference equation,
(Ref. Lapedes, A. & Farber, R.1987 Nonlinear Signal processing using
Networks : Prediction & System modelling, Tech. Rep. LA-UR-87-2662,
Los Alamos National Laboratory, Los Alamos, NM.)
c. Exit the DOS editor and observe the program running
d. Go to the "Examine Program Output" option and press <ret>
e. The program predicts that a network with 9 hidden units can be
trained with a MSE of .000987, and that networks with the proposed
structure should successfully generalize
f. You can run this program on your own data, simply by editing the
parameter file in the "batch Run" option.