Case context: A spam filter for a small email service is incorrectly marking many legitimate newsletters as spam. Rather than switching models immediately, you review a sample of the wrong predictions and group them by pattern, such as messages from new senders, promotional emails with many links, and short plain-text messages.

Question: What is the main outcome you are trying to achieve by studying these mistakes in this way?

Sample answer: The goal is to turn the mistakes into practical guidance for the next step. By examining the errors as if they were data, you can identify which kinds of emails are failing and decide what to improve first.

Key points:

• The review treats mistakes as a source of evidence.
• The purpose is to discover patterns in the failures.
• The result should guide the next model or data change.

Rubric: The student must state that the purpose of reviewing the misclassified emails is to learn what to do next to improve the model, especially by finding patterns in the errors.