MLS-C01 Modeling Practice Question
A data scientist is using Amazon SageMaker Autopilot to automatically build a binary classification model. The dataset has 50 features and 100,000 rows. After the experiment completes, the best candidate model achieves an F1 score of 0.85 on the validation set. However, when deployed to a real-time endpoint, the model's F1 score drops to 0.72 on production data. The data distributions between training and production are similar. What is the MOST likely cause of the performance drop?
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
✓
The Autopilot pipeline used features that are not available at inference time (data leakage).
Data leakage during Autopilot's feature engineering can lead to overly optimistic validation scores because features may have been derived from the target variable or from future information. Option A is wrong because similar distributions suggest no drift. Option B is wrong because Autopilot handles missing values. Option C is irrelevant because inference instance type does not affect model accuracy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Concept drift occurred between training and production.
Why it's wrong here
The stem states distributions are similar, so drift is unlikely.
- ✗
The production data contains missing values that were not present in training.
Why it's wrong here
Autopilot handles missing values, and this would be consistent.
- ✗
The inference endpoint uses a different instance type than training.
Why it's wrong here
Instance type does not affect model accuracy.
- ✓
The Autopilot pipeline used features that are not available at inference time (data leakage).
Why this is correct
If Autopilot used future information or features derived from the target, the validation score would be inflated.
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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.