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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of creating a baseline model in regression?
💡 Hint: Think about how we compare new models.
Question 2
Easy
Define Mean Squared Error (MSE).
💡 Hint: What does MSE reflect about model accuracy?
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 is the primary purpose of establishing a baseline model?
- To achieve the highest accuracy possible
- To compare with future models
- To eliminate noise
💡 Hint: Consider how we measure improvements in model performance.
Question 2
True or False: A high R-squared value always indicates a good model fit.
- True
- False
💡 Hint: Think critically about R-squared in context.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Suppose after running your baseline model, you discover a very low training MSE and a high test MSE. Discuss potential strategies to improve the model's generalization ability.
💡 Hint: Think about how to modify the model for better adaptability.
Question 2
You have a dataset with multiple features. Explain how each feature's significance might affect the outcome of the baseline regression model.
💡 Hint: Evaluate the impact of each predictor.
Challenge and get performance evaluation