Artificial Neural Network (ANN) can be used as a classification and prediction algorithm. Figure 9 shows genes dataset with actual and predicted class after ANN classification. Cancerous gene is denoted as l'or positive, whereas non-cancerous gene is denoted as '0' or negative. w 1.3 Gene 1 Gene 2 Gene 3 Gene 4 Actual Class Predicted Class 5.1 3.5 1.4 0.2 1 1 4.9 3 1.4 0.2 1 0 6.3 3.3 6 2.5 1 0 5.8 2.7 5.1 1.9 0 0 5 3.6 1.4 0.2 0 0 5.4 3.9 1.7 0.4 0 0 4.6 3.4 1.4 0.3 1 1 6.1 2.8 4.7 1.2 1 1 6.4 2.9 4.3 o 0 6.61 3 4.4 1.4 1 1 6.8 2.8 1.4 1 1 6.7 3 5 1.7 0 1 6 2.9 4.5 1.5 0 1 3.2 5.1 2 0 0 6.4 2.7 5.3 1.9 0 0 6.8 3 5.5 2.1 1 1 5.4 3.9 1.3 0.4 1 1 5.1 3.5 1.4 0.3 0 1 5.7 3.8 1.7 0.3 0 0 5.1 3.8 1.5 0.3 0 1 Figure 9: Classification result using ANN 3 2 4.8 6.5 . w lin Based on the dataset given in Figure 9, answer the following questions: a) Quantify the amount of True Positive (TP), True Negative (TN), False Positive (FP) and False Negative (FN) for the classification result [6 marks] b) Using your answers in 5a), calculate the accuracy, precision and recall for this classification [8 marks)