Suppose that a decision tree model has been built for a two-class classification problem in a two-dimensional space. The decision boundaries as shown in the figure below, where x and y represent the two axes of the space, and x, y 0. Suppose that five samples, as shown in the table below, are used to testify the performance of the classifier. YA 3 1 0 Yes class No class Yes class 10.5 0 1 1.5 2 2.5 3 ID x 1 2 3 4 5 y 0.6 0.2 0.7 0.9 1 0.7 1.5 2 3 3 Class Label Yes No Yes Yes No (a) Produce a confusion matrix for this classifier with all the appropriate elements. You must clearly show how you get your answer. (14 marks) (b) What are the true positive rate and the true negative rate of the classifier with the given test samples? You must clearly show how you get your answer. (6 marks) (c) Based on the decision boundaries provided, give the decision rules that the decision tree represents and sketch the decision tree. (10 marks) (d) Produce a diagram of a multilayer feedforward neural network (MFNN) with a single hidden layer that can be used to form the required decision boundaries via proper training. Your answer should include appropriate inputs and output of the network. (5 marks) Total: 35 Marks