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Answer: Precision and recall estimates based on a sample of messages flagged by the model as potentially inappropriate each minute
The correct answer is D. Precision and recall are critical metrics for evaluating the performance of classification models. Precision helps ensure that the model minimizes the burden on human moderators by not flagging too many false positives. Recall ensures that the model is effective at catching as many inappropriate messages as possible. Monitoring precision and recall estimates based on a sample of messages flagged by the model as potentially inappropriate each minute provides a clear measure of the model's real-world performance in identifying inappropriate content.
Author: LeetQuiz Editorial Team
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You work for a large social network service provider where users post articles and discuss news. With millions of comments posted daily, over 200 human moderators constantly review and flag inappropriate comments. Your team is tasked with building a machine learning (ML) model to assist human moderators in reviewing content on the platform. The ML model scores each comment and flags suspicious ones for human review. Which metric(s) should you use to monitor the performance of the ML model effectively?
A
Number of messages flagged by the model per minute
B
Number of messages flagged by the model per minute confirmed as being inappropriate by humans.
C
Precision and recall estimates based on a random sample of 0.1% of raw messages each minute sent to a human for review
D
Precision and recall estimates based on a sample of messages flagged by the model as potentially inappropriate each minute
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