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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define Mean Squared Error (MSE).
💡 Hint: Think about the errors in predictions.
Question 2
Easy
What does a higher R² Score indicate?
💡 Hint: Consider how it relates to model fit.
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 lower Mean Squared Error suggest?
- Worse model fit
- Better model fit
- No effect
💡 Hint: Think about the relationship between error and fit.
Question 2
The R² Score can be between which values?
- 0 to 1
- -1 to 1
- Any value
💡 Hint: Consider the meaning of a perfect prediction.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a model with predictions [100, 150, 200, 250] and actual values [110, 145, 195, 270], calculate both MSE and R² Score. Discuss the significance of these scores.
💡 Hint: Use the formulas for MSE and R² to find the answers.
Question 2
You created a linear regression model with a very low R² Score. What steps would you take to investigate potential improvements?
💡 Hint: Think about model assumptions and data quality.
Challenge and get performance evaluation