MLS-C01 · Question #140
MLS-C01 Question #140: Real Exam Question with Answer & Explanation
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Question
A data scientist must build a custom recommendation model in Amazon SageMaker for an online retail company. Due to the nature of the company's products, customers buy only 4-5 products every 5-10 years. So, the company relies on a steady stream of new customers. When a new customer signs up, the company collects data on the customer's preferences. Below is a sample of the data available to the data scientist. How should the data scientist split the dataset into a training and test set for this use case?
Options
- AShuffle all interaction data.
- BIdentify the most recent 10% of interactions for each user.
- CIdentify the 10% of users with the least interaction data.
- DRandomly select 10% of the users.
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