4 - Evaluating Regression Models
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Practice Questions
Test your understanding with targeted questions
Define Mean Absolute Error and explain its significance in regression.
💡 Hint: Consider how it treats positive and negative errors.
What does a lower RMSE indicate about a regression model?
💡 Hint: Think about the average error of predictions.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does MAE stand for in regression evaluation?
💡 Hint: Think about what 'absolute' means in relation to errors.
True or False: A higher R² score indicates a better model fit.
💡 Hint: Consider what higher values suggest about a model's explanatory power.
1 more question available
Challenge Problems
Push your limits with advanced challenges
A regression model predicts home prices based on area. Actual prices are $300k, $450k, and $500k, while predicted values are $320k, $430k, and $480k. Calculate the MAE, MSE, and RMSE.
💡 Hint: Break the calculations into steps; calculate absolute errors first, then square them.
You have two models with R² scores: Model A (0.85) and Model B (0.60). What can you infer about the models' performances in explaining variance?
💡 Hint: Focus on what higher R² scores imply regarding model effectiveness.
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