MATLAB Answers

How can two neural networks be compared for regression based on training and testing results ?

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Kangujam
Kangujam on 23 Aug 2018
Answered: Greg Heath on 4 Feb 2019
How can two neural networks be compared for regression based on training and testing results ?

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Greg Heath
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
Kangujam
Kangujam on 24 Aug 2018
@Greg Heath actually after implementation of neural network for regression, training and testing MSE results will be obtained. So from those neural networks, which mse has to be chosen for comparison? Will it be training mse or testing mse?

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Answers (2)

BERGHOUT Tarek
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
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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