This is a sample question from the certification preparation for advanced predictive modeling:
Consider a Generalized Additive Neural Network (GANN) with 3 continuous inputs and 2 hidden nodes
for each input.
How many parameters do you need to estimate when training the neural network?
A. 19
B. 21
C. 22
D. 25
correct_answer = "C"
I would like to know why the correct answer is C? Is there a formula that could be used to calculate the parameters estimated in GANN or can someone please draw a diagram to illustrate the correct answer? Thanks.
Hello,
I think (!) it's like this :
So, 3 continuous inputs with each of them having two hidden nodes (in one hidden layer) and a skip layer ... that makes:
3 * (3 * 2 + 1) + 1 = 22
Koen
Thanks for the explanation!
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