how to predict from a trained neural network ?
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Hello I am trying to use neural network to make some prediction based on my input and target data. I have read all related tutorial in Matlab and also looked at the matlab examples. I kinda learned how to develop a network but I dont know how to use this train network to make some prediction ? is there any code that im missing ? does anyone have a sample script that can be shared here?
that's what I have, for example : x=[1 2 3;4 5 3] t=[0.5 0.6 0.7] , net=feedforwardnet(10) , net=train(net,x,t) , perf=perform(net,y,t)
how can I predict the output for a new set of x (xprime=[4 2 3;4 7 8]) based on this trained network? thanks
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Accepted Answer
Greg Heath
on 16 Jan 2018
1. Your code should yield an error because you have not defined y.
here are two ways to define output y, error e and normalized mean square error NMSE (= 1-Rsquare)
1. [ net tr ] = train(net,x,t);
y = net(x);
e = t-y;
2. [ net tr y e ] = train(net,x,t); % My favorite
then, in general,
NMSE = mse(e)/mean(var(t',1))
or for 1-dimensional outputs
NMSE = mse(e)/var(t,1)
Hope this helps.
Greg
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More Answers (1)
Mritula C
on 14 Feb 2019
Hi How do you predicted with a new test class?
1 Comment
Greg Heath
on 15 Feb 2019
- You misplaced your commented question into an Answer Box.
- This is a regression prolem. Your question involves classification.
Greg
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