Question 120 of 835
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MLA-C01 Practice Question: A data scientist is training a binary…
A data scientist is training a binary classification model using a dataset that has a severe class imbalance (90% negative, 10% positive). Which technique should be used to address the imbalance during model training?
⚠ Common exam trap
AWS often tests the misconception that hyperparameter tuning (like batch size or learning rate) can fix data imbalance, when in fact only data-level or algorithm-level techniques (e.g., oversampling, undersampling, or cost-sensitive learning) directly address the skewed class distribution.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Apply random oversampling of the minority class
Random oversampling of the minority class (Option C) directly addresses class imbalance by duplicating or synthesizing examples from the positive class, which balances the training distribution and prevents the model from becoming biased toward the majority class. This technique is specifically designed to mitigate the skewed gradient updates that occur when the minority class is underrepresented, leading to better recall and precision for the positive class in binary classification tasks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a larger batch size
Why it's wrong here
Larger batch size does not address class imbalance; it may even exacerbate it by providing fewer minority examples per batch.
- ✗
Use L2 regularization
Why it's wrong here
L2 regularization prevents overfitting but does not address class imbalance.
- ✓
Apply random oversampling of the minority class
Why this is correct
Random oversampling balances the class distribution by replicating minority class samples.
- ✗
Increase the learning rate
Why it's wrong here
Increasing learning rate can affect convergence but does not correct class imbalance.
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Last reviewed: Jun 30, 2026
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.
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