Practice The Apriori Algorithm (Conceptual Steps) - 13.3.4 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 13) | Machine Learning
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13.3.4 - The Apriori Algorithm (Conceptual Steps)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the Apriori property?

💡 Hint: Think about how subsets relate to their parent set.

Question 2

Easy

Define Support in the context of the Apriori algorithm.

💡 Hint: Consider what percentage of your dataset needs to have this itemset for it to be considered frequent.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does the Apriori property state?

  • If an itemset is frequent
  • all subsets are frequent
  • An itemset must contain all items to be frequent
  • All supersets of an infrequent itemset are frequent

💡 Hint: Think about how subsets relate to their parent set.

Question 2

True or False: Support is the proportion of transactions that contain the entire itemset.

  • True
  • False

💡 Hint: Consider what 'support' really implies in terms of transactions.

Solve 3 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Using a dataset of at least 10 transactions, illustrate the Apriori algorithm by calculating the support, confidence, and lift for a small itemset. Present your findings.

💡 Hint: Set up a transaction matrix and systematically work through calculating the support first.

Question 2

Discuss the trade-offs of using a low support threshold versus a high support threshold in the Apriori algorithm. What are the consequences on the number of rules generated?

💡 Hint: Think about the advantages and disadvantages of finding more data versus potential overfitting on less significant rules.

Challenge and get performance evaluation