Apriori Algorithm MCQs

By: Prof. Dr. Fazal Rehman Shamil | Last updated: August 7, 2024

1. What is the primary purpose of the Apriori algorithm in data mining?
a) Classification
b) Regression
c) Association rule mining
d) Clustering

Answer: c) Association rule mining

2. Which of the following is the first step in the Apriori algorithm?
a) Generate candidate itemsets
b) Calculate confidence
c) Prune non-frequent itemsets
d) Generate frequent itemsets

Answer: a) Generate candidate itemsets

3. In the context of the Apriori algorithm, what is ‘support’?
a) The ratio of the number of transactions that contain an itemset to the total number of transactions
b) The probability of an itemset occurring given another itemset
c) The strength of an association rule
d) The total number of items in a transaction

Answer: a) The ratio of the number of transactions that contain an itemset to the total number of transactions

4. How does the Apriori algorithm generate candidate itemsets?
a) By randomly selecting items
b) By using frequent itemsets from the previous iteration
c) By clustering similar items
d) By sorting items based on their frequency

Answer: b) By using frequent itemsets from the previous iteration

5. What is the purpose of the pruning step in the Apriori algorithm?
a) To generate new candidate itemsets
b) To remove infrequent itemsets
c) To calculate the confidence of rules
d) To sort the itemsets

Answer: b) To remove infrequent itemsets

6. In the Apriori algorithm, which property helps reduce the number of candidate itemsets?
a) Monotonicity property
b) Anti-monotonicity property
c) Transitivity property
d) Symmetry property

Answer: b) Anti-monotonicity property

7. What does the ‘confidence’ measure in the context of association rules?
a) The frequency of the rule in the dataset
b) The accuracy of the rule
c) The probability that the rule’s consequent is true given the antecedent
d) The number of items in the rule

Answer: c) The probability that the rule’s consequent is true given the antecedent

8. If an itemset is frequent, what can be said about its subsets in the context of the Apriori algorithm?
a) They must also be frequent
b) They can be infrequent
c) They are irrelevant
d) They are less important

Answer: a) They must also be frequent

9. What does the term ‘lift’ indicate in association rule mining?
a) The number of items in a transaction
b) The strength of a rule over random occurrence
c) The total number of transactions
d) The sum of item frequencies

Answer: b) The strength of a rule over random occurrence

10. Which of the following is a limitation of the Apriori algorithm?
a) It cannot handle large datasets
b) It requires multiple database scans
c) It does not support numeric data
d) It cannot generate rules with more than two items

Answer: b) It requires multiple database scans

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