PLEASE DO NOT USE THE NEWGROUP AND ANSWERS FOR THE SAME PROBLEM!!!
I have stuck with using narnet .
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Yeasir Mohammad Akib
am 21 Dez. 2015
Kommentiert: Greg Heath
am 27 Dez. 2015
I have used the code provided by Greg in newsgroup. My sample code is here:
Input
clc,clear;
plt=0;
X=load('BOD test.txt');
L=length(X),
net=narnet(1:.1,10);
view(net),
[Xs,Xsi,Asi,Ts] = preparets( net, {}, {}, X );
ts = cell2mat(Ts);
plt = plt+1; figure(plt), hold on
plot( 1:L, ts, 'LineWidth', 2 )
rng( 'default' )
[net tr Ys Es Af Xf] = train( net, Xs, Ts, Xsi, Asi );
view( net )
NMSEs = mse( Es ) /var( ts,1 )
ys = cell2mat( Ys );
plot( 1:L, ys, 'ro', 'LineWidth', 2 )
axis( [ 0 22 0 1.3 ] )
legend( 'TARGET', 'OUTPUT' )
title( 'OPENLOOP NARNET RESULTS')
And the output is:
L =
18
NMSEs =
1.0000
And what's wrong with curve plot:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/152809/image.png)
4 Kommentare
Greg Heath
am 27 Dez. 2015
I understand your point. However, often the descriptions of the same problem from the same poster in the two forums are different.
Consequently I have found myself dizzily ping ponging back and forth between the two.
It is very, very annoying.
Therefore, I will continue, at least for neural nets, to rant my dissatisfaction. However, I will add a neural net qualifier.
Grumpy Greg
Akzeptierte Antwort
Greg Heath
am 26 Dez. 2015
net = narnet(1:.1,10);
1:0.1 is an error
However, I do not think that you have enough data to do what you wish.
Any further communication should be made via the NEWSGROUP.
Greg
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