Matlab Neural networks: why use sim?
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After the network has been trained, there seem to be two different ways to utilize the network to make predictions:
(1) test_outputs = net(test_inputs)
(2) test_outputs = sim(net, test_inputs)
What is the difference, and which is better?
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