Practice Recall (Sensitivity or True Positive Rate) - 5.3.4 | Module 3: Supervised Learning - Classification Fundamentals (Weeks 5) | Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define recall in your own words.

πŸ’‘ Hint: Think about how it relates to identifying true positives.

Question 2

Easy

What is the formula for recall?

πŸ’‘ Hint: Remember the relationship between true positives and false negatives.

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 recall measure?

  • The proportion of false positives
  • The proportion of actual positives correctly identified
  • The overall accuracy of the model

πŸ’‘ Hint: Focus on the 'true positive' aspect.

Question 2

True or False: Recall is also known as the false positive rate.

  • True
  • False

πŸ’‘ Hint: Revisit the definitions we've discussed.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You have a model that predicts whether an email is spam. It correctly identified 70 spam emails but missed 30. Calculate the recall and interpret its result.

πŸ’‘ Hint: Calculate using the recall formula.

Question 2

Discuss how you would improve recall in a fraud detection system without significantly impacting user experience.

πŸ’‘ Hint: Think of strategies that balance detection with user satisfaction.

Challenge and get performance evaluation