AWS Certified Big Data – Specialty — Question 41

An administrator tries to use the Amazon Machine Learning service to classify social media posts that mention the administrators company into posts that require a response and posts that do not. The training dataset of
10,000 posts contains the details of each post including the timestamp, author, and full text of the post. The administrator is missing the target labels that are required for training.
Which Amazon Machine Learning model is the most appropriate for the task?

Answer options

• A. Binary classification model, where the target class is the require-response post
• B. Binary classification model, where the two classes are the require-response post and does-not-require- response
• C. Multi-class prediction model, with two classes: require-response post and does-not-require-response
• D. Regression model where the predicted value is the probability that the post requires a response

Correct answer: A

Explanation

The correct answer is A because a binary classification model effectively identifies whether a post requires a response or not by focusing on the target class that needs to be predicted. Option B, while also a binary classification model, introduces unnecessary complexity by mentioning two classes instead of focusing on a single target class. Options C and D are not suitable as they suggest multi-class prediction and regression, which are not appropriate for this binary classification scenario.