Practice Evaluation Metrics (3.3) - Supervised Learning - Regression & Regularization (Weeks 3)
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Evaluation Metrics

Practice - Evaluation Metrics

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does MSE measure?

💡 Hint: Think about how the errors are treated in this metric.

Question 2 Easy

True or False: RMSE is the square root of MSE.

💡 Hint: Remember the relationship between these two metrics.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does MSE stand for?

Mean Squared Error
Mean Standard Error
Mean Scaled Error

💡 Hint: Remember the emphasis on squaring errors.

Question 2

Is RMSE sensitive to outliers?

True
False

💡 Hint: Consider how squaring impacts larger values.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You predict a student’s test scores based on study hours. The actual scores are [75, 85, 90] for predictions of [70, 88, 91]. Calculate MSE, RMSE, and MAE.

💡 Hint: Apply the respective formulas for MSE, RMSE, and MAE.

Challenge 2 Hard

A regression model for predicting sales has an R² of 0.5. Discuss what this might imply about the model and its predictors.

💡 Hint: Consider what the percentage tells you about the predictive power of the model.

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Reference links

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