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A data scientist is using association rule mining with the Apriori algorithm on customer purchase data in Snowflake to identify product bundles. After generating the rules, they obtain the following metrics for a specific rule: Support = 0.05, Confidence = 0.7, Lift = 1.2. Consider that the overall purchase probability of the consequent (right-hand side) of the rule is 0.4. Which of the following statements are CORRECT interpretations of these metrics in the context of business recommendations for product bundling?
Correct Answer: A,D,E
Option A is correct because support represents the proportion of transactions that contain both the antecedent and the consequent. Option D is correct because confidence represents the proportion of transactions containing the antecedent that also contain the consequent. Option E is correct because lift = confidence / (probability of consequent). Therefore, lift of 1.2 means confidence is 1.2 times the probability of the consequent. Hence 20% more likely than the baseline. Option B is incorrect because lift, not confidence, captures the relative likelihood compared to the baseline. Option C is incorrect because a lift > 1 suggests a positive correlation, not a negative one.