Question: Machine learning neural networks Exercise 3 : Multilayer Perceptron Consider a two-layer perceptron that uses the linear function f(x) = z as activation instead of

Machine learning neural networks

Machine learning neural networks Exercise 3 : Multilayer Perceptron Consider a two-layer

Exercise 3 : Multilayer Perceptron Consider a two-layer perceptron that uses the linear function f(x) = z as activation instead of the sigmoid function (2). Assume that there are p = 2 attributes in the feature space, that the hidden layer has 1 = 2 units, and that the output layer has k = 1 units. In other words, the network output y(x) is determined by the following expression: y(x) = - f(wio + win y +wizy) f(wio + win f(wo + wi-11+w12-12)+w 2. f(w%. + wi- 11 +w52 - 12) = 11 21 Will this network be able to learn a solution to the XOR problem? Justify your answer formally

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