Association Rules for Bookstore Transactions. Leggere, an Internet book retailer, is interested in better understanding the purchase decisions of its customers. For a set of 2,000 customer transactions, it has categorized the individual book purchases comprising those transactions into one or more of the following categories: Novels, Willa Bean series, Cooking Books, Bob Villa Do-It-Yourself, Youth Fantasy, Art Books, Biography, Cooking Books by Mossimo Bottura, Harry Potter series, Florence Art Books, and Titian Art Books. Leggere has conducted association rules analysis on this data set and would like to analyze the output. Based on a minimum support of 200 transactions and a minimum confidence of 50%, the table below shows the top 10 rules with respect to lift ratio. a. Explain why the top rule "If customer buys a Bottura cooking book, then they buy a cooking book," is not helpful even though it has the largest lift and 100% confidence. b. Explain how the confidence of 52.99% and lift ratio of 2.20 was computed for the rule "If a customer buys a cooking book and a biography book, then they buy an art book. Interpret these quantities. c. Based on these top 10 rules, what general insight can Leggere gain on the purchase habits of these customers? d. What will be the effect on the rules generated if Leggere decreases the minimum support and reruns the association rules analysis? e. What will be the effect on the rules generated if Leggere decreases the minimum confidence and reruns the association rules analysis?