Association Rules DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   Which statement best defines an association rule in data mining?

   • AA rule that predicts the future value of a continuous variable based on past observations
   • BA rule that assigns each transaction to a predefined category based on historical labels
   • CA rule that groups similar transactions together based on feature similarity
   • DA rule that expresses a conditional implication of the form X → Y, where X and Y are disjoint itemsets
   Reveal Solution Discussion Select an answer first
2. 7application · medium

   A data mining team is running the Apriori algorithm on a transaction database. They set the minimum support to 0.01 and the minimum confidence to 0.5. After the algorithm completes, they notice that many rules have very low support but high confidence. What is the most likely reason for this?

   • AThe transaction database is too small, causing statistical noise.
   • BThe minimum support threshold is set too low, allowing rare itemsets to generate rules.
   • CThe algorithm is incorrectly implemented, as high confidence cannot occur with low support.
   • DThe minimum confidence threshold is set too high, filtering out rules with high support.
   Reveal Solution Discussion Select an answer first
4. 8application · medium

   A data analyst is evaluating association rules for a recommendation system. They have two rules: Rule A: {Coffee} → {Milk} with confidence = 0.8 and lift = 1.1. Rule B: {Coffee} → {Sugar} with confidence = 0.6 and lift = 2.5. Which rule is more interesting for a recommendation?

   • ARule A, because higher confidence means the rule is more reliable.
   • BRule B, because the higher lift indicates a stronger association beyond chance.
   • CBoth rules are equally interesting because they have the same antecedent.
   • DNeither rule is interesting because lift values are too low.
   Reveal Solution Discussion Select an answer first
5. 9foundation · easy

   In the context of market basket analysis, what is the primary purpose of an association rule?

   • ATo segment customers into distinct groups based on their demographic characteristics
   • BTo predict the exact quantity of each item a customer will purchase in a future transaction
   • CTo identify items that are frequently purchased together, enabling insights for cross-selling and product placement
   • DTo rank individual items by their total sales revenue in descending order
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6. 10application · medium

   A supermarket chain is analyzing transaction data. They find that 5% of all transactions include both bread and butter. The probability of a transaction containing butter is 10%, and the probability of a transaction containing bread is 20%. What is the lift of the rule {Bread} → {Butter}?

   • A2.5
   • B0.25
   • C0.5
   • D1.0
   Reveal Solution Discussion Select an answer first