This problem does not require the use of data mining software and focuses on knowledge of concepts and basic calculations.

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 20% of transactions and a minimum confidence of 50%, the table below shows the top 10 rules with respect to lift ratio.

Antecedent	Consequent	Support for A & C	Confidence	Lift Ratio
BotturaCooking	Cooking	0.227	1.00	1.16
Cooking, BobVilla	Art	0.205	0.54	1.12
Cooking, Art	Biography	0.204	0.61	1.10
Cooking, Biography	Art	0.204	0.56	1.10
Youth Fantasy	Novels, Cooking	0.245	0.55	1.075
Cooking, Art	BobVilla	0.205	0.61	1.055
Cooking, BobVilla	Biography	0.218	0.58	1.04
Biography	Novels, Cooking	0.293	0.53	1.035
Novels, Cooking	Biography	0.293	0.57	1.035
Art	Novels, Cooking	0.249	0.52	1.01

(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 56% and lift ratio of 1.10 was computed for the rule "If a customer buys a cooking book and a biography book, then they buy an art book." (Round your answers to the three decimal places.)

confidence:

0.204/ x = 0.56

lift ratio:

0.56/ x = 1.10

(d)

What will be the effect on the rules generated if Leggere decreases the minimum support and reruns the association rules analysis?

Decreasing the minimum support will generate a ---Select--- smaller larger pool of rules and therefore will likely result in association rules with ---Select--- smaller larger lift ratios. A rule with this kind of lift ratio would suggest that it is ---Select--- effective ineffective at identifying transactions in which the consequent occurs. However, the transactions involving the item set of the association rule ---Select--- may not occur as will occur more frequently due to the lowered minimum support. Thus, the association rule may apply to ---Select--- too few transactions to be a very large number of transactions, making it a valuable business opportunity.

(e)

What will be the effect on the rules generated if Leggere decreases the minimum confidence and reruns the association rules analysis?

Decreasing the minimum confidence will generate a ---Select--- smaller larger pool of rules and therefore likely result in association rules with ---Select--- smaller larger lift ratios. A rule with this kind of lift ratio would suggest that it is ---Select--- effective ineffective at identifying transactions in which the consequent occurs. If this rule has a low confidence, then there also is a ---Select--- high low probability that the consequent will occur given the antecedent. That is, as the confidence of an association rule decreases, the relationship between the antecedent and consequent will ---Select--- fail succeed more often. Depending on the profit margin associated with the transaction, this may make the association rule ---Select--- an extremely not a viable business opportunity.