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CD ROM Paradise Collection 4
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CD ROM Paradise Collection 4 1995 Nov.iso
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science
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neumap3.zip
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NUMP.ZP
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INI.HLP
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1994-09-03
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47 lines
Fast Training Program;
1. Purpose;
a. Initialize a MLP using random initial weights
b. Train a MLP network using a method much faster than BP
2. Features;
a. Uses a batching approach, so the order of training
patterns is unimportant
b. Has adaptation of learning factor
c. Shows training MSE and error percentages
d. Does not save weights to the disk, in the demo version
3. Example Run of Fast Training Program
a. Go to the "Batch Processing" option and press <ret>
b. Observe the parameter file with commented keyboard responses;
10, .0005 ! Enter number of iterations, MSE threshold
2 ! Enter 1 for old weights, 2 to initialize with random weights
gls.top ! file storing network structure
gls ! filename for training data
1 ! 1 if the data file contains desired outputs, 2 else
0 ! Enter number of patterns to read (0 for all training patterns)
0, 0 ! Enter numbers of 1st and last patterns to examine (0 0 for none)
.03 ! learning factor
gls1.wts ! filename for saving the trained weights
4 ! 1 to continue training, 2 to start new network, 3 for a new data file, 4 to stop
The program will read all patterns from the file gls, and train a MLP
using the network structure file gls.top, which is shown below.
4
4 5 2 1
1 1 1
The network will have 4 layers including 4 inputs, 7 hidden units
divided between 2 hidden layers, and 1 output. In addition, layers 2,
3, and 4 connect to all previous layers. Training will stop
after 10 iterations, or when the MSE % reaches .0005 . The final
network weights will be stored in the file gls1.wts.
c. Exit the DOS editor and observe the program running
d. Go to the "Examine Program Output" option and press <ret>
e. You can run this program on your own data, simply by editing the
parameter file in the "batch Run" option.