how to make a neural network with a large matrix as inputs?
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Amalia
el 14 de Oct. de 2014
Comentada: Greg Heath
el 17 de Oct. de 2014
this is the code:
Ptr=xlsread('liaa(16s).xlsx','sheet1','I3:I402');
T=xlsread('liaa(16s).xlsx','sheet1','G3:G402');
net=newff(Ptr,T,4,{'logsig','purelin'},'trainlm','learngdm');
[net,tr]=train(net,Ptr,T);
y=sim(net,Ptr)
plot(Ptr,T,'bo',Ptr,y,'r*');
title('Perbandingan antara Target (o) dan Output Jaringan (*)');
xlabel('input');
and the errors said:
??? Error using ==> plus
Matrix dimensions must agree.
Error in ==> calcperf2 at 163
N{i,ts} = N{i,ts} + Z{k};
Error in ==> trainlm at 253
[perf,El,trainV.Y,Ac,N,Zb,Zi,Zl] = calcperf2(net,X,trainV.Pd,trainV.Tl,trainV.Ai,Q,TS);
Error in ==> network.train at 219
[net,tr] = feval(net.trainFcn,net,tr,trainV,valV,testV);
Error in ==> training_lia_vt at 11
[net,tr]=train(net,Ptr,T);
Both Ptr and T are 400x1 matrix, and i couldn't get the program to run unless the matrix get transposed. but if transpose the matrix the results i get is reversed. i'm supposed to get a graphic like this one:
but instead the result is:
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Respuesta aceptada
Greg Heath
el 14 de Oct. de 2014
1. The matrices should be transposed.
2. there are 5 relevant plots
a. input vs time
b. target vs time
c. target vs input
d. output superimposed on b
e. output superimposed on c
Hope this helps.
Thank you for formally accepting my answer
Greg
2 comentarios
Greg Heath
el 17 de Oct. de 2014
1x400 is correct. If your results are backwards use fliplr.
You can plot your results any way you want.
Greg
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