How to tune the regularization parameter in extreme learning machine?
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I train ELM on my dataset and gives test accuracy of 92.13. I wonder how to tune parameters to gain more test accuracy?
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BERGHOUT Tarek
2019-2-3
if you want to get beter trainig accuracy in basic SLFN traind by ELM you should do this:
1- invrease the nuber of neurons one by one using incrimental ELM until the networks gives a stable accuracy
2- after that you can change the formula of beta "B=pinv(H)*T" to this one
(B=(inv((I/C)+H'*H)*H'*T);
wher I is the identity matrix you can type "help eye " in Matlab;
and try yo make your hidden layers as a squered matrix.
and after that you can increase your regularization parameter C incrimentaly until you get the minimam training error.
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BERGHOUT Tarek
2019-2-4
if you want to get beter trainig accuracy in basic SLFN traind by ELM you should do this:
1- invrease the nuber of neurons one by one using incrimental ELM until the networks gives a stable accuracy
2- after that you can change the formula of beta "B=pinv(H)*T" to this one
(B=(inv((I/C)+H'*H)*H'*T);
wher I is the identity matrix you can type "help eye " in Matlab;
and try yo make your hidden layers as a squered matrix.
and after that you can increase your regularization parameter C incrimentaly until you get the minimam training error.
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