Microsoft Azure AI Fundamentals (AI-900) Practice Exam

Which term describes the calculated probability of a correct image classification?

1. Precision

2. Recall

3. Accuracy

4. F1 Score

The correct answer is: Accuracy

The term that describes the calculated probability of a correct image classification is accuracy. Accuracy measures the proportion of true results (both true positives and true negatives) among the total number of cases examined. In the context of image classification, it indicates how often the model correctly identifies the images out of all the images it processed. For instance, if a model classifies 80 out of 100 images correctly, its accuracy would be 80%. This metric provides a straightforward way to understand the effectiveness of the model in making correct predictions, which is particularly useful in scenarios where the classes are balanced. Precision, recall, and F1 score are also important metrics used to evaluate model performance, but they serve different purposes. Precision focuses on the correctness of positive predictions, recall measures the model's ability to identify all relevant instances, and the F1 score is the harmonic mean of precision and recall, providing a balance between the two. However, none of these terms directly reflect the overall probability of correct classification across both classes, making accuracy the clear choice for this specific inquiry.