how to predict from a trained neural network ?

5 views (last 30 days)
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

Accepted Answer

Greg Heath
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

More Answers (1)

Mritula C
Mritula C on 14 Feb 2019
Hi How do you predicted with a new test class?
  1 Comment
Greg Heath
Greg Heath on 15 Feb 2019
  1. You misplaced your commented question into an Answer Box.
  2. This is a regression prolem. Your question involves classification.
Greg

Sign in to comment.

Categories

Find more on Sequence and Numeric Feature Data Workflows in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!