Question
An ML engineer needs to use an ML model to predict the price of apartments in a specific location.
Which metric should the ML engineer use to evaluate the model's performance?
- A. Accuracy
- B. Area Under the ROC Curve (AUC)
- C. F1 score
- D. Mean absolute error (MAE) Correct
Explanation
The correct answer is D, Mean Absolute Error (MAE). This metric is appropriate for regression tasks where the goal is to predict a continuous value, such as apartment prices. MAE measures the average magnitude of errors between predicted and actual values without considering their direction, making it suitable for evaluating model performance in this context.
