Microsoft Azure AI Fundamentals — Question 98

What are two metrics that you can use to evaluate a regression model? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

Answer options

• A. coefficient of determination (R2)
• B. F1 score
• C. root mean squared error (RMSE)
• D. area under curve (AUC)
• E. balanced accuracy

Correct answer: A, C

Explanation

The coefficient of determination (R2) measures the proportion of variance in the dependent variable that can be predicted from the independent variables, making it a key metric for regression. Root mean squared error (RMSE) quantifies the average error in predictions, providing insight into model accuracy. The F1 score, area under curve (AUC), and balanced accuracy are metrics more relevant to classification tasks, not regression.