Question 1

What is the purpose of the Apriori algorithm?

Accepted Answer

To discover frequent item sets in a dataset

Answer

To classify data into predefined categories

Answer

To perform association rule mining

Answer

To predict future values based on historical data

Question 2

What is the minimum support threshold in the Apriori algorithm?

Accepted Answer

The minimum frequency or percentage of occurrence for an item set to be considered frequent

Answer

The minimum number of transactions in the dataset

Answer

The number of distinct items in the dataset

Answer

The maximum number of iterations allowed in the algorithm

Question 3

What is the confidence measure used in association rules generated by the Apriori algorithm?

Accepted Answer

The conditional probability of the consequent given the antecedent

Answer

The support of the antecedent

Answer

The confidence of the antecedent

Answer

The lift of the association rule

Question 4

What is the pruning technique used in the Apriori algorithm?

Accepted Answer

The downward closure property

Answer

The breadth-first search

Answer

The upward closure property

Answer

The random sampling

Question 5

What is the aim of the frequent itemset mining task?

Accepted Answer

To discover sets of items that frequently co-occur in a dataset

Answer

To identify the most valuable items in a dataset

Answer

To sort the items in a dataset based on their frequencies

Answer

To predict future itemsets based on historical data

Question 6

What is the candidate generation step in the Apriori algorithm?

Accepted Answer

The process of generating candidate item sets of higher order based on the frequent item sets of lower order

Answer

The process of selecting the most frequent item sets from the dataset

Answer

The process of determining the association rules

Answer

The process of calculating the support for each item set

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