- A
The feature is no longer relevant to predictions
Why wrong: An increase in SHAP value suggests the feature has become more important, not less.
- B
A bug in the SHAP computation
Why wrong: While possible, the most likely and actionable interpretation is concept drift.
- C
Data drift in that feature
Why wrong: Data drift would manifest as a change in the input distribution, which is not observed here.
- D
Concept drift in the model
SHAP attribution drift indicates that the model's reliance on features has changed, which is a sign of concept drift.
Question 198 of 1,000
MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance, and security. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses SageMaker Model Monitor's feature attribution drift monitoring with SHAP. They receive an alert that the average SHAP value for a particular feature has increased significantly compared to the baseline. The feature's input distribution has not changed. What does this likely indicate?
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
✓
Concept drift in the model
SHAP values measure the contribution of each feature to the model's predictions. A change in SHAP values while input distribution is stable suggests the model has learned a new reliance on that feature, i.e., the relationship between the feature and the target has changed — concept drift.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The feature is no longer relevant to predictions
Why it's wrong here
An increase in SHAP value suggests the feature has become more important, not less.
- ✗
A bug in the SHAP computation
Why it's wrong here
While possible, the most likely and actionable interpretation is concept drift.
- ✗
Data drift in that feature
Why it's wrong here
Data drift would manifest as a change in the input distribution, which is not observed here.
- ✓
Concept drift in the model
Why this is correct
SHAP attribution drift indicates that the model's reliance on features has changed, which is a sign of concept drift.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Solution Monitoring, Maintenance, and Security — This question tests ML Solution Monitoring, Maintenance, and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Concept drift in the model — SHAP values measure the contribution of each feature to the model's predictions. A change in SHAP values while input distribution is stable suggests the model has learned a new reliance on that feature, i.e., the relationship between the feature and the target has changed — concept drift.
What should I do if I get this MLA-C01 question wrong?
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 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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