Answer-first summary for fast verification
Answer: Recall, because it directly measures the proportion of actual spam emails that were correctly identified by the model.
Recall is the correct metric for this scenario because it measures the proportion of actual positives (real spam emails) that were correctly identified by the model. This is crucial for ensuring that as many spam emails as possible are caught, aligning with the primary goal of minimizing spam in users' inboxes. While precision (D) is important for reducing false positives (legitimate emails marked as spam), the immediate priority is to catch all spam emails, making recall the more relevant metric. Accuracy (A) and F-Score (B) provide broader measures of model performance but do not specifically address the need to identify all real spam emails.
Author: LeetQuiz Editorial Team
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In the context of developing a spam email classification model for a large email service provider, you are tasked with selecting the most appropriate metric to evaluate the model's performance. The primary goal is to ensure that the model accurately identifies as many real spam emails as possible, minimizing the risk of spam emails reaching users' inboxes. Given the constraints of handling millions of emails daily and the need for real-time processing, which metric should you prioritize to accurately measure the percentage of real spam emails that were correctly recognized by the model? Choose the best option.
A
Accuracy, as it provides a general measure of the model's correctness across all classifications.
B
F-Score, since it balances the trade-off between precision and recall, offering a single metric for model evaluation.
C
Recall, because it directly measures the proportion of actual spam emails that were correctly identified by the model.
D
Precision, as it focuses on the proportion of emails classified as spam that are indeed spam, reducing false positives.
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