MLS-C01 Modeling Practice Question
A data scientist builds a Random Forest model using SageMaker. The model performs well on training data but poorly on test data. Which step is most likely to reduce overfitting?
⚠ Common exam trap
Watch out — candidates often assume adding more trees (Option B) always improves generalization, but they miss that overfitting in Random Forest is primarily caused by individual trees being too deep, not by the ensemble size.
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
✓
Reduce the maximum depth of each tree
Reducing the maximum depth of each tree limits the complexity of individual decision trees, preventing them from memorizing noise and specific patterns in the training data. This directly addresses overfitting by enforcing simpler, more generalized splits, which improves performance on unseen test 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.
- ✓
Reduce the maximum depth of each tree
Why this is correct
Shallower trees reduce model complexity and help prevent overfitting.
- ✗
Increase the number of trees
Why it's wrong here
More trees generally reduce variance but may still overfit if trees are deep.
- ✗
Switch to a linear model
Why it's wrong here
Linear model may underfit; not a direct fix for overfitting.
- ✗
Increase the number of features considered at each split
Why it's wrong here
More features can increase correlation among trees and overfitting.
Go deeper
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.