Question 4. (4 marks). Consider the following transaction database: Transaction ID Items {avocado, berries, broccoli, garlic} {avocado, berries, broccoli, garlic} (berries, coconuts} {avocado, coconuts} {avocado, broccoli, coconuts} { coconuts} {berries, broccoli, coconuts} {berries, broccoli } 9 {avocado, berries, broccoli, coconuts, garlic} 10 {avocado, berries, broccoli, coconuts, garlic} 11 {avocado, coconuts} 12 {avocado, garlic} 13 {avocado, broccoli, coconuts, garlic} 14 {avocado, broccoli, garlic} (a) Determine all one-item and two-item item-sets with minimum support 0.4. Show all steps of your working. (b) Use your answer to (a) to determine all three-item item-sets with minimum support 0.4. (c) Use your previous answers to determine all association rules with minimum support 0.4 which would be con- structed by the Apriori algorithm. Calculate the confidence and lift for each rule you find, presenting your final answer in table form. Show each division you performed in the table, but do not spend too much time writing detailed working out. For example, your entries under the confidence and lift columns should look something like "0.123/0.456 = 0.270" but with different numbers. (d) Of the rules you found in part (c), which would be the best predictor of cross-sales? Justify your answer, with reference to the calculations in part (c). Complete Question 4 by hand, showing all working. Give your answers to at least 3 decimal places. Hint: although the work you submit must be done by hand, it is recommended that you check your answers using R. 2 of 2