PREDICTED YES NO ACTUAL YES NO 28 4 6 a. In your own words, explain what a confusion matrix is. (4) b. In the confusion matrix above, the values in the diagonal are high (28 and 24), what does that tell you about the accuracy of the model that has this confusion matrix? 24 (4) c. What do high values for False Positive and False negative mean? Explain (4) (4) d. Explain one example in which a high number of False Positives would have serious consequences. e. Explain one example in which a high number of False Negatives would have serious consequences. (4) . 3.2 Given a simple artificial neural network that does not have a hidden layer, compute the output value given the following information: . There are 3 inputs(x1 = 30, x2 = 18, x3 = -40) and the value of the bias (b) is 3 The weights of the 3 inputs are +0.35, +0.21 and -0.25 respectively (10)