Why is predicting the output of a trained neural network by using "net/sim" different than manually calculating the output using the network weights, biases and transfer functions?
%%create random data
rng(1);
xdata = rand(5,100);
ydata = rand(1,100);
%%fit a forward network
nlayersize = 10;
net = feedforwardnet(nlayersize);
net.trainParam.showWindow = false;
net = train(net,xdata,ydata);
net.layers{1}.transferFcn
%%calculate the model output at a new point
xNew = rand(5,1);
y1 = net(xNew); % can use sim as well
%%manually calculate model output
IW = net.IW{1};
LW = net.LW{2,1};
b = net.b;
y2 = IW*xNew+b{1};
y2 = tansig(y2);
y2 = LW*y2+b{2};
dy = y1-y2
John Williams answered . 2024-05-18 05:16:08
xNew = rand(5,1);
y1 = net(xNew);
xNew = mapminmax('apply', xNew , net.inputs{1}.processSettings{1}); % apply input pre-processing
IW = net.IW{1};
LW = net.LW{2, 1};
b = net.b;
y2 = IW*xNew+b{1};
y2 = tansig(y2);
y2 = LW*y2+b{2};
y2 = mapminmax('reverse', y2, net.outputs{2}.processSettings{1}); % reverse the output pre-processing
dy = y1 - y2
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