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 Q3. Table Q3 Subject Classifier output score 0.73 Ground Truth 1 0 0 0 1 1 1 1 0 10 OOOOOOO 0 0 NBARUNG DOWN - 13 14 0 1 16 17 0.18 0.43 0.18 0.73 0.91 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 0.39 0.5 0.97 0.57 0.23 0.21 0.83 0.56 1 19 20 1 22 23 OOOOOOO 0 25 26 27 0 30 0 (a) (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, F1 score, accuracy, TP rate, and FP rate with respect to the chosen threshold value. [20 marks) (b) How would you arrange the dataset for your learning algorithm training, cross validation, and testing? Justify your