Question: cs 188 So Many Derivatives! 10 Points Grading comment: Consider the neural network configuration below: neuralnetwork.jpg Question 2.1 Q2.1 2 Points Grading comment: Which of

cs 188 So Many Derivatives! 10 Points Grading comment: Consider the neural network configuration below: neuralnetwork.jpg Question 2.1 Q2.1 2 Points Grading comment: Which of the following decision boundaries can be learned by the neural network? Assume w o , w 1 , x 0 , x 1 , T a R n w o ,w 1 ,x 0 ,x 1 ,T a R n and z = w 0 x 0 w 1 x 1 z=w 0 x 0 w 1 x 1 . Let g ( z ) g(z) be the binary step activation function with T a T a as the decision threshold, which is defined as follows: function.jpg graphs.jpg Choice 1 of 5: Graph A Choice 2 of 5: Graph B Choice 3 of 5: Graph C Choice 4 of 5: Graph D Choice 5 of 5: Graph E

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