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I've just builded a neural net with 2 input and 1 output neurons, the hidden layer works fine with 20 neurons. The object is to predict porosity values from gamma ray and electrical induction inputs. I've been asked to explain why did I used 20 neurons in the hidden layer. Is there some mathematical background or empirical relation to determine the number of these neurons? Less neurons give poor results and the more neurons I add the slower the program runs. Thanks in advance
Manolo
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