Q47 — AWS AIF-C01 Ch.1

Question 47 of 100 | ← Chapter 1

An AI developer has built a deep learning model to classify material types in images. Now, the AI developer wants to measure the model’s performance. Which metric can help the AI developer evaluate the model’s performance?

• A. Confusion matrix ✓
• B. Correlation matrix
• C. R² score
• D. Mean squared error (MSE)

Correct Answer: A. Confusion matrix

Explanation

This question tests knowledge of metrics for evaluating deep learning models. A confusion matrix clearly shows per-class prediction outcomes—including true positives, true negatives, false positives, and false negatives—enabling comprehensive assessment of classification performance (e.g., precision, recall, F1-score). A correlation matrix measures linear relationships between variables and is unsuitable for classification evaluation. R² score and MSE are regression-specific metrics and do not apply to categorical classification tasks. Therefore, option A, 'confusion matrix,' is the appropriate metric for evaluating an image classification model.