AI-102 Question 149
Single answerYou have trained a custom vision model for classifying images into three categories: 'Cat', 'Dog', and 'Bird'. During evaluation, the model achieves a precision of 85% and recall of 70%. Which metric would you choose to best evaluate the balance between precision and recall, and what does it represent?
- A
Accuracy - Represents the proportion of correctly classified images out of the total images.
- B
F1 Score - Represents the harmonic mean of precision and recall.
- C
Precision - Represents the proportion of correctly classified positive cases out of all predicted positive cases.
- D
Recall - Represents the proportion of correctly classified positive cases out of all actual positive cases.
Show answer and explanation
Correct answer: B
Explanation
The F1 Score is specifically designed to provide a balanced evaluation of a model's performance by considering both precision and recall. It is particularly useful when the dataset is imbalanced or when both false positives and false negatives carry significant consequences. In this scenario, as the precision and recall are not equal, the F1 Score is the most appropriate metric to understand the model's performance comprehensively.
- A. Incorrect.
Accuracy is not the best metric in this scenario because it does not account for the balance between precision and recall, especially when there is an imbalance in the dataset or misclassification costs vary.
- B. Correct.
F1 Score is the correct answer because it combines both precision and recall into a single metric, providing a balanced evaluation of the model's performance when both are important.
- C. Incorrect.
Precision, while useful, only focuses on the positive predictions and does not consider the model's ability to identify all relevant positive cases, making it incomplete for this scenario.
- D. Incorrect.
Recall focuses solely on the model's ability to identify all positive cases and does not consider the false positives, which makes it insufficient for evaluating the balance between precision and recall.