Imagine you have a network that is trying to predict a categorical response with three levels (categories) and uses a softmax activation function on the final layer. If there is just one node in the...


Imagine you have a network that is trying to predict a categorical response with three levels (categories) and uses a softmax activation function on the<br>final layer. If there is just one node in the L-1 layer and that node has an activation value of 5 for a particular observation, use the parameters given<br>below to calculate the probability of the observation being in class 1. The probability is<br>0 : (W = -0.2; W = 0.4; W{} = 0.1, bf = 0.3, bị = -0.2, bg = 0.8<br>O A. 0.05<br>O B. 0.59<br>O C. 0.33<br>O D. 0.36<br>

Extracted text: Imagine you have a network that is trying to predict a categorical response with three levels (categories) and uses a softmax activation function on the final layer. If there is just one node in the L-1 layer and that node has an activation value of 5 for a particular observation, use the parameters given below to calculate the probability of the observation being in class 1. The probability is 0 : (W = -0.2; W = 0.4; W{} = 0.1, bf = 0.3, bị = -0.2, bg = 0.8 O A. 0.05 O B. 0.59 O C. 0.33 O D. 0.36

Jun 04, 2022
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