# How can I call network

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Hazim Hamad on 2 May 2021
Commented: Jon Cherrie on 6 May 2021
I am using nueral network to prdict the output of four inputs ( x1,...x4)
I need to call the netowrk from another matlab file currently i am using save and load the net but this method takes time to load the net do you know any alternative method to call the net please.
x=data(:,1:4)
y=data(:,5)
m=length(y);
Visulaisation of the data
histogram(y,10)
Normalise the features and transform the output
y2=log(1+y)
histogram(y2,10)
plot(x(:,2),y2,'o')
Normalise the input variables
for i=1:4
x2(:,i)=(x(:,i)-min(x(:,i)))/(max(x(:,i))-min(x(:,i)))
end
Train an artificial neural network (ANN)
rng default % For reproducibility
xt=x2'
yt=y2'
hiddenLayerSize=16;
net=fitnet(hiddenLayerSize)
net.divideParam.trainratio=70/100;
net.divideParam.valratio=30/100;
net.divideParam.testratio=0/100;
[net,tr]=train(net,xt,yt)
performance of N.N
yTrain=exp(net(xt(:,tr.trainInd)))-1
yTrainTrue=exp(yt(:,tr.trainInd))-1
sqrt(mean((yTrain-yTrainTrue).^2))
yVal=exp(net(xt(:,tr.valInd)))-1
yValTrue=exp(yt(:,tr.valInd))-1
sqrt(mean((yVal-yValTrue).^2))
gregnet1 = net;
save gregnet1

Jon Cherrie on 2 May 2021
You can use the sim function:
The sim function is usually called implicitly by calling the neural network as a function. For instance, these two expressions return the same result:
y = sim(net,x)
y = net(x)
I think for your case, you need something like this:
x=data(:,1:4)
y=data(:,5)
net = gregnet1;
% Evaluate network on data
xt = x.';
yhat = exp(net(xt)-1).';
% Compare predictions with new data
ytrue = y;
sqrt(mean((yhat-yTrainTrue).^2))
If you want to use the sim function instead of net(xt), then replace the "yhat =" line with
yhat = exp( sim(net,xt) - 1).';
##### 2 CommentsShowHide 1 older comment
Jon Cherrie on 6 May 2021
This is an important topic and perhaps too long to cover in answer here. You might be better off with the documentation, e.g., starting from

R2020a

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