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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a confusion matrix?
π‘ Hint: Think about how we assess correctness in classification tasks.
Question 2
Easy
What is the purpose of the F1 score?
π‘ Hint: Consider both correct and incorrect classifications in your response.
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 main purpose of a confusion matrix?
π‘ Hint: Think about how model accuracy is represented.
Question 2
True or False: F1 score is useful when dealing with imbalanced datasets.
π‘ Hint: Reflect on how correct classifications impact evaluations.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
Your model's confusion matrix shows that it struggles to classify a specific class correctly while performing well on others. Discuss the steps you would take to improve its performance.
π‘ Hint: Consider both data-related and technical adjustments.
Question 2
You have noticed the residual plot shows a significant pattern indicating systematic errors. How would you address this in your regression analysis?
π‘ Hint: Think about model adaptability in line with observed data trends.
Challenge and get performance evaluation