Which visual tool displays the counts of correct and incorrect predictions across categories?

• A. Confusion matrix
• B. Accuracy
• C. Precision
• D. Recall

Answer: (A)

A confusion matrix visually presents the counts of correct and incorrect predictions across categories. It’s a grid where actual categories run along one axis and predicted categories along the other, and each cell shows how many samples fall into that actual-predicted combination. The diagonal cells represent correct predictions, while off-diagonal cells reveal which categories are being confused with others. This per-category breakdown helps you see where the model struggles and how misclassifications are distributed, especially in multi-class tasks.

Accuracy, precision, and recall are numerical summaries rather than visual grids of counts. Accuracy gives an overall rate of correct predictions, but hides where errors happen. Precision and recall focus on specific aspects of positive class performance and are typically reported as numbers per class, not as a single visual map of all category interactions.