please answer the questions if you can. It will be really appreciated a lot. thank you

27. From Q26, with your out, create a confusion matrix and calculate True Positives (TP), False Positives (FP), True Negatives (TN), False Negatives (FN), Accuracy, Precision, Recall, and Specificity. Show all your steps. 28. From Q26, what is the output of a 5-NN (nearest neighbor classifier)? Calculate Accuracy and compare it with the accuracy of 1-NN. Which one is more accurate? Show all your steps. 29. Cluster the following eight points (with (x,y) representing locations) into three clusters: A1(2, 10), A2(2, 5), A3(8, 4), A4(5, 8), A5(7, 5), A6(6,4), A7(1,2),A8(4,9) Initial cluster centers are: A1(2,10),A4(5,8) and A7(1,2). The distance function (called Manhattan distance) between two points a=(x1,y1) and b=(x2,y2) is defined as D(a,b)=x2x1+y2y1 Use K-Means Algorithm to find the three cluster centers after the second iteration. 30. You are working with a database table that contains invoice data. The table includes columns for customer_id and total (total amount billed for each invoice). Some customers have multiple invoices. You want to find out the total amount billed to each customer, and store the result in a new column as total_amoint. Write SQL query. (Hint; add a GROUP BY clause that will group the data by customer ID number.)