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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does a confusion matrix display?
π‘ Hint: Think of how many predictions were right or wrong.
Question 2
Easy
Why is accuracy sometimes a misleading metric?
π‘ Hint: Consider cases where one outcome is rare.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the primary purpose of a confusion matrix?
π‘ Hint: Think about what classifications are being compared.
Question 2
True or False: A high accuracy always indicates a good model performance.
π‘ Hint: Remember cases where accuracy can be misleading.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Given a dataset where the classifier has an accuracy of 90% but precision is 50% and recall is 75%, analyze its performance.
π‘ Hint: Think about what each metric tells you about user experience.
Question 2
A model is used for fraud detection with a 70% accuracy but has a recall of only 30%. What does this suggest about the model's performance in catching fraud cases?
π‘ Hint: Consider how much of the target class is being missed by the model.
Challenge and get performance evaluation