Question 3 (20 marks) Given the following 8 points in 3 dimensions: (1,1,0), (2,1,0), (4,3,1), (5,4,2), (-1,0.-1), (3,3,

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Question 3 20 Marks Given The Following 8 Points In 3 Dimensions 1 1 0 2 1 0 4 3 1 5 4 2 1 0 1 3 3 1 (83.37 KiB) Viewed 24 times

Question 3 (20 marks) Given the following 8 points in 3 dimensions: (1,1,0), (2,1,0), (4,3,1), (5,4,2), (-1,0.-1), (3,3,2), (-1,2,2), (3,3,3) perform k-means clustering algorithm of k=2 clusters with Manhattan distance for these 8 points. Use (1,1,0) and (3,3,2) as the initial means. You must show working steps until the results show no change between steps; guess work will gain no mark. (Round your answers off to 5 decimal places). Question 4 (20 marks) Given the following transaction database: Transaction ID items T1 I1, 12, 13 T2 12, 13, 14 T3 14, 15 T4 II, 12, 14 T5 I1, 12, 13, 15 T6 I1, 12, 13, 14 17 12, 14, 15 T8 12, 13, 14 T9 T10 11 2 14, 15 (a) What is the output of the Apriori algorithm run on the above transaction database with a minimum support of 50% (i.e. 3 out of 6 transactions)? (b) Based on the frequent itemsets found in (a), list out all the association rules in which only item {13} is in the consequent. (c) Assuming that minimum confidence = 30%, calculate which rules in (b) are strong. (d) Calculate the LIFT: L( XY), for the following association rules: L(11-12), L(1415), L(11-14), L(12-13)