Neural network (NN)
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Kerrollenna Martta
el 6 de Oct. de 2022
Comentada: Walter Roberson
el 22 de Oct. de 2022
Hi. I have problem to train my Neural Network. This is the coding.
clear
clc
load c.mat
load OUTPUT1.mat
inputrain = c(1:1000,:);
targetrain = OUTPUT1(1:1000);
[pn,mininputrain,maxinputrain,tn,mintargetrain,maxtargetrain] = premnmx(inputrain,targetrain);
net=newff(minmax(pn),[20,10,1],{'logsig','logsig','purelin'},'trainlm');
net=init(net);
net.trainParam.show = 1;
net.trainParam.lr = 0.9;
net.trainParam.mc = 0.9;
net.trainParam.epochs = 1000;
net.trainParam.goal = 1e-3;
net = train(net,pn,tn);
an = sim(net,pn);
[a] = postmnmx(an,mintargetrain,maxtargetrain);
result_norm = [an' tn'];
result_denorm = [a' targetrain'];
error = mse(tn-an);
mape = mean(abs(error./tn));
rmse = sqrt(mean((error - tn).^2));
[m,b,r] = postreg(a,targetrain);
save net.mat net
The error said " Output data size does not match net.outputs{3}.size." Help me please. Thank you
2 comentarios
Respuesta aceptada
Walter Roberson
el 6 de Oct. de 2022
Editada: Walter Roberson
el 6 de Oct. de 2022
net=newff(minmax(pn),[20,10,1],{'logsig','logsig','purelin'},'trainlm');
You are missing a parameter. The {'logsig'} and so on vector must be the 4th parameter. The first three parameters must be P, T, S where P is input vectors, T is target vectors, and S is sizes of the input layers. S can be [] if you want it to be calculated based upon the sizes of the entries in T.
2 comentarios
Walter Roberson
el 22 de Oct. de 2022
premnmx was obsoleted in R2006a, so it is difficult to find documentation for it.
I suspect that maybe you should use
net=newff(pn, tn, [20,10,1], {'logsig','logsig','purelin'}, 'trainlm');
but newff() was obsoleted in R2010b . You should probably modernize the code.
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