Question 1,617 of 1,672
MLS-C01 Modeling Practice Question
A company uses Amazon SageMaker to train a linear regression model. During evaluation, they observe that the model has high bias (underfitting). Which THREE actions can reduce bias?
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
✓
Add polynomial features.
Options B, C, and E are correct. Bias (underfitting) occurs when the model is too simple to capture patterns in the data. Adding polynomial features (B) increases model complexity, allowing the linear regression to fit non-linear relationships. Reducing regularization strength (C) reduces the penalty on large coefficients, letting the model fit the training data more closely. Using a random forest model (E) is a more complex algorithm capable of capturing non-linear patterns, thus reducing bias. Option A (increasing L2 regularization) increases bias by penalizing large weights. Option D (using a smaller training dataset) typically increases bias due to less data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase L2 regularization.
Why it's wrong here
Increasing regularization increases bias by penalizing large coefficients.
- ✓
Add polynomial features.
Why this is correct
Polynomial features increase model capacity, reducing bias.
- ✓
Reduce the regularization strength.
Why this is correct
Lower regularization allows the model to fit the training data more closely, reducing bias.
- ✗
Use a smaller training dataset.
Why it's wrong here
Less data usually leads to higher bias, not lower.
- ✓
Use a random forest model instead of linear regression.
Why this is correct
Random forest is more complex and can reduce bias if linear assumptions are violated.
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Last reviewed: Jun 20, 2026
This MLS-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 MLS-C01 exam.
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