1. Functions of the Network Structure Estimation Program
 a. This program examines the training data and;
 b. Requests a minimum acceptable classification error 
    percentage from the user. A typical number is one 
    between 0 and 10.
 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;

GRNG          ! data filename
16            ! number of inputs per pattern 
3             ! minimum acceptable error percentage (0 to 10, usually)
8             ! maximum allowable number of iterations

    Here, we will estimate the required size of an MLP for 
    classifying geometric shapes (elipses, triangles, 
    quadrilaterals, and pentagons.
 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 13 hidden units, in 
    two hidden layers, can have a classification error percentage
    of 2.375.
 f. You can run this program on your own data, simply by editing the 
    parameter file in the "batch Run" option.
  