MLS-C01 Modeling Practice Question
A company has deployed a real-time inference endpoint using SageMaker for a fraud detection model. The model uses a Random Forest classifier. The endpoint receives predictions but the latency is too high. The metric shows p99 latency of 500ms, but the requirement is under 200ms. The team has already optimized the instance type to the maximum allowed by their budget. The data scientist suggests: A) Reducing the number of trees in the Random Forest model. B) Switching to a linear model like Logistic Regression. C) Enabling SageMaker's batch transform instead of real-time endpoint. D) Adding more instances to the endpoint behind a load balancer. Which option will MOST effectively reduce latency while maintaining acceptable accuracy?
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 number of trees in the Random Forest model
(Reducing the number of trees) is the most effective method to reduce latency while maintaining acceptable accuracy. Fewer trees directly decrease inference time of the Random Forest model, although it may slightly impact accuracy. Switching to a linear model (Option A) would reduce latency but likely result in significant accuracy loss. Batch transform (Option C) is not suitable for real-time inference. Adding more instances (Option D) improves throughput but not per-request latency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch to a linear model like Logistic Regression
Why it's wrong here
Linear models are faster but may have much lower accuracy for fraud detection.
- ✓
Reduce the number of trees in the Random Forest model
Why this is correct
Fewer trees mean faster inference, though accuracy may drop slightly; it's a direct latency reduction.
- ✗
Enable SageMaker's batch transform
Why it's wrong here
Batch transform is for offline predictions, not real-time.
- ✗
Add more instances to the endpoint
Why it's wrong here
More instances improve throughput but not per-request latency; each request still processed by one instance.
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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.