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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define True Positive.
💡 Hint: Think about the examples used in emails.
Question 2
Easy
What is a False Negative?
💡 Hint: Consider what happens when a spam email is missed.
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 a True Positive indicate?
- Correctly predicted negative class
- Incorrectly predicted positive class
- Correctly predicted positive class
💡 Hint: Consider the meaning of true versus false.
Question 2
Is a False Positive a good indicator of model performance?
- True
- False
💡 Hint: Think of how it affects users.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Suppose a new spam detection model is tested on 500 emails, resulting in 200 True Positives, 50 False Positives, 100 True Negatives, and 150 False Negatives. Calculate accuracy, precision, recall, and F1 score.
💡 Hint: Make sure to use the correct formulas for each metric.
Question 2
You have a dataset with 80 instances labeled positive and 20 labeled negative. The model predicts all instances as positive. Is this a good strategy? What is the confusion matrix and the derived metrics?
💡 Hint: Reflect on the implications of missing actual negative cases.
Challenge and get performance evaluation