How can I use the trained weights of a neural network

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How can I use the trained weights of a neural network to simulate the output of a classification problem?

Accepted Answer

David Franco
David Franco on 1 Oct 2020
I found the answer (output and yy are equal):
% Simulated a Neural Network
clear
close
clc
rng default
[x,y] = simpleclass_dataset;
neurons = 10;
net = feedforwardnet(neurons);
net = train(net,x,y);
outputs = sim(net,x);
% outputs = round(outputs);
figure, plotconfusion(y,outputs)
w1 = net.IW{1,1};
w2 = net.LW{2,1};
b1 = net.b{1};
b2 = net.b{2};
xx = x;
for ii = 1:length(net.inputs{1}.processFcns)
xx = feval(net.inputs{1}.processFcns{ii},...
'apply',xx,net.inputs{1}.processSettings{ii});
end
a1 = tanh(w1*xx + b1);
yy = purelin(w2*a1 + b2);
for mm = 1:length(net.outputs{1,2}.processFcns)
yy = feval(net.outputs{1,2}.processFcns{mm},...
'reverse',yy,net.outputs{1,2}.processSettings{mm});
end
figure, plotconfusion(y,yy)
=)

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