Provided the classifier output score made by a learning algorithm from the dataset comprises of 30 subjects and the respective ground truth as shown in Table 03. Table Q3 Ground Truth 1 0 0 0 Classifier output score 0.73 0.18 0.43 0.18 0.73 1 1 0 0.91 1 1 Subject 1 2 3 4 5 6 7 B 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 OOOOOO 0.42 0.71 0.94 0.47 0.57 0.06 0.17 0.08 0.06 0.82 0.78 0.06 0.72 0.03 0.52 0.87 1 1 0 1 0 1 1 0 0 1 0 0 0 1 0 0.39 0.5 0.97 0.57 0.23 0.21 0.83 0.58 (a) The final step of the designed learning algorithm is to determine the optimum threshold value. Clearly show the steps involved in calculating the precision, recall, Fi score accuracy, TP rate, and FP rate with respect to the chosen threshold value. [20 marks] How would you arrange the dataset for your learning algorithm training, cross validation, and testing? Justify your answer. [5 marks) (b) Provided the classifier output score made by a learning algorithm from the dataset comprises of 30 subjects and the respective ground truth as shown in Table 03. Table Q3 Ground Truth 1 0 0 0 Classifier output score 0.73 0.18 0.43 0.18 0.73 1 1 0 0.91 1 1 Subject 1 2 3 4 5 6 7 B 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 OOOOOO 0.42 0.71 0.94 0.47 0.57 0.06 0.17 0.08 0.06 0.82 0.78 0.06 0.72 0.03 0.52 0.87 1 1 0 1 0 1 1 0 0 1 0 0 0 1 0 0.39 0.5 0.97 0.57 0.23 0.21 0.83 0.58 (a) The final step of the designed learning algorithm is to determine the optimum threshold value. Clearly show the steps involved in calculating the precision, recall, Fi score accuracy, TP rate, and FP rate with respect to the chosen threshold value. [20 marks] How would you arrange the dataset for your learning algorithm training, cross validation, and testing? Justify your answer. [5 marks) (b)