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How can two neural networks be compared for regression based on training and testing results ?
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How can two neural networks be compared for regression based on training and testing results ?
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Greg Heath
on 23 Aug 2018
Edited: Greg Heath
on 23 Aug 2018
Since it is obvious that 2 nets can be compared by plotting their reponses, it is unclear what your problem is.
Please elucidate.
Greg
Answers (2)
BERGHOUT Tarek
on 3 Feb 2019
for regression the lower error the greater accuracy is the network gets . you can also use a T test for you output analysis to determine which net is better
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Greg Heath
on 4 Feb 2019
The MATLAB default is training/validation/testing fractions of 0.7/0.15/0.15
Typically, the performance depends on a
1. A reasonable choice for number of hidden layers and nodes
2. A successful choice of RANDOM division into train/val/test subsets
3. A successful group of RANDOM initial weights
MY APPROACH:
1. A single hidden layer
2. Loop over 0 to Hmax trial values for numHidden
3. 10 random initial weight trials for each test value of H
4. MSEgoal = 0.01*mean(var(target',1))
NETWORK GRADING
grade = alpha*MSEtst + beta*MSEval
If N is sufficiently large alpha = 1, beta = 0
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