AWS Certified Machine Learning Engineer - Associate MLA-C01 — Topic 1 Question 208

Question

An ML engineer is collecting data to train a classification ML model by using Amazon SageMaker AI. The target column can have two possible values: Class A or Class B. The ML engineer wants to ensure that the number of samples for both Class A and Class B are balanced, without losing any existing training data. The ML engineer must test the balance of the training data. Which solution will meet this requirement?

Accepted Answer

Correct answer: B. The correct answer is B. Option B: Use SageMaker Clarify to check for class imbalance (CI). If the value is greater than 0, then use synthetic minority oversampling technique (SMOTE) in SageMaker Data Wrangler to balance the classes. Amazon SageMaker builds, trains and deploys machine learning models in a fully managed service.

AWS Certified Machine Learning Engineer - Associate MLA-C01 — Question 208