Association Rules DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 3)

Questions 11–15

1. 11application · medium

   A data analyst is working with a transaction dataset. They find that the support for {Bread} → {Butter} is 0.03, and the support for {Bread} is 0.10. What is the confidence of the rule {Bread} → {Butter}?

   • A0.03
   • B0.30
   • C0.33
   • D0.10
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2. 12foundation · easy

   In the Apriori algorithm, what is the first step in generating association rules from frequent itemsets?

   • ACompute the lift for every possible rule directly from the transaction data
   • BSort all items by their confidence in descending order
   • CFind all frequent itemsets that meet a minimum support threshold
   • DGenerate all possible itemsets and then filter by support
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4. 13application · medium

   A business analyst is considering using association rules to analyze customer purchase patterns. They want to identify products that are frequently bought together. Which statement best describes the output of association rule mining?

   • AA set of decision trees that classify customers into buyers and non-buyers.
   • BA set of clusters of customers with similar purchasing habits.
   • CA set of time series forecasts predicting future sales.
   • DA set of rules in the form {X} → {Y}, where X and Y are itemsets, indicating that transactions containing X are likely to contain Y.
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5. 14application · medium

   A data scientist is using the Apriori algorithm to mine frequent itemsets from a large retail transaction database. The algorithm is taking too long to run. Which modification would most directly reduce the computational cost while still producing valid frequent itemsets?

   • ADecrease the minimum support threshold to allow more itemsets to be considered.
   • BIncrease the minimum confidence threshold to filter rules after itemset generation.
   • CIncrease the minimum support threshold to prune more candidate itemsets early.
   • DUse a larger transaction database to improve the statistical significance of the itemsets.
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6. 15application · medium

   A data scientist is using the Apriori algorithm to find association rules. They want to ensure that the rules generated are statistically significant. Which approach is most appropriate?

   • ASet a maximum confidence threshold to avoid overfitting.
   • BUse only rules with a support of 1.0 to guarantee significance.
   • CIgnore lift and only use confidence to evaluate rules.
   • DSet a minimum lift threshold to filter out rules that do not show a strong association beyond chance.
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