Using data in the table below, construct a Neural Network with one Output Layer (z) and one Hidden Layer (two nodes A and B). Calculate the predicted outcome if the inputs to the input nodes are (Node 1=.4, Node 2=.7 Node 3= .7 and Node 4=.2) Use the actual value of .75 and a learning factor of .1 to adjust the weight for A to z. (Extra credit for using Matrix multiplication) From To Weight X A 0.5 Node 1 A 0.6 Node 2 A 0.8 Node 3 A 0.6 Node 4 A 0.2 x B 0.7 Node 1 B 0.9 Node 2 B 0.8 Node 3 B 0.4 Node 4 B 0.2 xx z 0.5 A z 0.9 B z 0.9
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For Node A: Weighted sum = (0.4 * 0.5) + (0.7 * 0.6) + (0.7 * 0.8) + (0.2 * 0.6) = 0.2 + 0.42 + 0.56 + 0.12 = 1.3 For Node B: Weighted sum = (0.4 * 0.2) + (0.7 * 0.7) + (0.7 * 0.9) + (0.2 * 0.8) = 0.08 + 0.49 + 0.63 + 0.16 = 1.36 Show more…
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