Practice Mean Absolute Error (MAE) - 3.3.3 | Module 2: Supervised Learning - Regression & Regularization (Weeks 3) | Machine Learning
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3.3.3 - Mean Absolute Error (MAE)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Calculate the MAE for actual values [10, 20, 30] and predicted values [12, 18, 29].

πŸ’‘ Hint: Use the absolute differences and divide by how many values there are.

Question 2

Easy

What does a lower MAE indicate?

πŸ’‘ Hint: Think about accuracy in predictions.

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 formula for MAE?

πŸ’‘ Hint: Recall what each component of the formula represents.

Question 2

True or False: MAE is more sensitive to outliers compared to MSE.

πŸ’‘ Hint: Consider how squaring affects error contribution.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset of actual sales: [120, 150, 200, 160] and predictions: [130, 145, 190, 155], calculate the MAE. What does this value indicate about the model's predictions?

πŸ’‘ Hint: Calculate individual absolute differences before averaging.

Question 2

In a real estate model, actual prices are [300k, 400k, 500k] and predicted prices are [310k, 420k, 490k]. What is the MAE, and how does it reflect the model's performance?

πŸ’‘ Hint: Sum the absolute differences and divide by the number of predictions.

Challenge and get performance evaluation