Info on Network Modeling and Pruning Program

1. Given a trained MLP network, the program;
 a. Models the net
 b. Measures its performance as a function of 
    the number of hidden units

2. The non-demo version of the program; 
 a. Prunes the net to a user-controlled size and saves a pruned 
      net to disk
 b. Determines the effective degree (amount of nonlinearity) of the net

3. Example Run of Network Modeling and Pruning Program
 a. Go to the "Batch Processing" option and press <ret>
 b. Observe the parameter file with commented keyboard responses;

grng.top            ! network structure file
2                   ! 1 if the outputs are coded, 2 for uncoded output format
grng                ! data file
0                   ! number of training patterns (0 for all data) 
0, 0                ! Enter numbers of 1st and last patterns to examine (0 0 for none)
grng1.wts           ! weight file of trained network
7.0                 ! Maximum acceptable classification error percentage in pruned network


    The program will prune the network from the fast training program,
    which has network structure file grng.top and weight file grng1.wts,
    so that it has 7 % classification error or less.
 c. Exit the DOS editor and observe the program running
 d. Go to the "Examine Program Output" option and press <ret>
 e. The program has created a new network, having 10 hidden units,
    which performs about as well as the original network.
 f. You can run this program on your own data, simply by editing the 
    parameter file in the "batch Run" option. Realistically, it is 
    more productive to use the "Manual Run" with this program.


