b) Assuming a single neuron as shown in the following diagram. Randomly assign the weights from the set {-1, +1}to the connections and assume threshold-based activation function. By applying forward pass, find out the predicted output (Y). Also, report the confusion matrix. X1 W1 ý = h W2 h X2 W3 X3 c) By assuming mean-square error (MSE) function and Ý obtained in (b), calculate the loss. d) Now change the activation function to sigmoid and use the same weights as defined in (b). Apply the forward pass, and obtain the predicted output (Ỹ) and confusion matrix. wo

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
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b) Assuming a single neuron as shown in the following diagram. Randomly assign the weights from
the set {-1, +1} to the connections and assume threshold-based activation function. By applying
forward pass, find out the predicted output (Ỹ). Also, report the confusion matrix.
Wo
X1
W1
ý = h
W2
X2
W3
X3
c) By assuming mean-square error (MSE) function and Y obtained in (b), calculate the loss.
d) Now change the activation function to sigmoid and use the same weights as defined in (b).
Apply the forward pass, and obtain the predicted output (Ý) and confusion matrix.
wo
Transcribed Image Text:b) Assuming a single neuron as shown in the following diagram. Randomly assign the weights from the set {-1, +1} to the connections and assume threshold-based activation function. By applying forward pass, find out the predicted output (Ỹ). Also, report the confusion matrix. Wo X1 W1 ý = h W2 X2 W3 X3 c) By assuming mean-square error (MSE) function and Y obtained in (b), calculate the loss. d) Now change the activation function to sigmoid and use the same weights as defined in (b). Apply the forward pass, and obtain the predicted output (Ý) and confusion matrix. wo
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