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:
% Read data
data = readmatrix("new_data.txt")
x=data(:,1:4)
y=data(:,5)
% Load saved network
load gregnet
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).';
