Question 6 [2 pts]: Given the following feedforward neural network with one hidden layer and one output layer, assuming the network initial weights are 1.0 [1.01 1.0 1 Wob Oc Oa 1.0. All nodes use a sigmoid activation function with |1.0 1.0 W. 1.0 Wib Wia ac 1.0 1.0 W. W W 2b value a-2.0, and the learning rate n is set to 0.5. The expected output is 1 if an instance's class label is “True”, otherwise, the expected output is 0. Given the following three instances /ı, l2, I3 which are labeled as “True”, “False”, and “True”, respectively, please calculate their actual outputs from the network? [0.5 pt What is the mean squared error of the network with respect to the three instances? [0.5 pt] Assuming instance is fed to the network to update the weight, please update the network weight (using backpropogation rule) by using this instance (list major steps and results). [1.0 pts] 1.01 1.01 1.0 I =0.5 | 0.5 7 = |1.0| |0.5 I, = | 0.0 1.0 Was ac Wia X Wib Figure 4

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