Quick Answer
The answer is to keep the threshold at 0.5. The model already achieves a recall of 95/100 = 0.95, meeting the requirement without any adjustment. Recall, also known as true positive rate, is calculated as TP/(TP+FN); here, with 95 true positives and only 5 false negatives out of 100 actual failures, the recall is exactly 0.95. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding that threshold adjustment for recall in SageMaker is only necessary when the current recall falls below the target—lowering the threshold increases recall by capturing more positives but often at the cost of precision. A common trap is assuming you must always lower the threshold to boost recall, but if recall is already sufficient, no change is needed. Memory tip: “Check recall first—if it’s already 95, keep the threshold alive.”
This MLS-C01 practice question tests your understanding of modeling. 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 is using Amazon SageMaker to deploy a machine learning model that predicts equipment failure. The model is a binary classifier that outputs a probability. The company wants to set a threshold such that the model correctly identifies 95% of actual failures (recall >= 0.95). The model's precision at the current threshold of 0.5 is 0.7. The data scientist evaluates the model on a test set and obtains the following confusion matrix at threshold 0.5: TP=95, FN=5, FP=40, TN=860. The total actual positives are 100. Which threshold adjustment should the data scientist make to achieve the recall goal?
Decrease the threshold to 0.1
Why wrong: Unnecessarily decreases precision.
Increase the threshold to 0.7
Why wrong: Increasing threshold would decrease recall, missing the goal.
Keep the threshold at 0.5
Recall is already 95%, meeting the requirement.
Decrease the threshold to 0.3
Why wrong: Decreasing threshold may increase recall but could reduce precision; recall is already at goal.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Keep the threshold at 0.5
Option B is correct. Lowering the threshold increases recall by classifying more instances as positive, which reduces false negatives. Currently recall is 95/100 = 0.95, so recall is already 95%. Actually, recall is already 95% at threshold 0.5. So the requirement is already met. But the question might imply that recall needs to be at least 95%, which it is. However, the stem says 'the company wants to set a threshold such that the model correctly identifies 95% of actual failures (recall >= 0.95)'. At threshold 0.5, recall is 95/100 = 0.95, so it meets the requirement. So no adjustment is needed. But the options include 'Keep the threshold at 0.5' as option D. So D is correct. Let me check: If recall is already 0.95, then no change needed. So answer D.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Decrease the threshold to 0.1
Why it's wrong here
Unnecessarily decreases precision.
Increase the threshold to 0.7
Why it's wrong here
Increasing threshold would decrease recall, missing the goal.
Keep the threshold at 0.5
Why this is correct
Recall is already 95%, meeting the requirement.
Related concept
Read the scenario before looking for a memorised answer.
Decrease the threshold to 0.3
Why it's wrong here
Decreasing threshold may increase recall but could reduce precision; recall is already at goal.
Common exam traps
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
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.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
Identify which MLS-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
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
The correct answer is: Keep the threshold at 0.5 — Option B is correct. Lowering the threshold increases recall by classifying more instances as positive, which reduces false negatives. Currently recall is 95/100 = 0.95, so recall is already 95%. Actually, recall is already 95% at threshold 0.5. So the requirement is already met. But the question might imply that recall needs to be at least 95%, which it is. However, the stem says 'the company wants to set a threshold such that the model correctly identifies 95% of actual failures (recall >= 0.95)'. At threshold 0.5, recall is 95/100 = 0.95, so it meets the requirement. So no adjustment is needed. But the options include 'Keep the threshold at 0.5' as option D. So D is correct. Let me check: If recall is already 0.95, then no change needed. So answer D.
Identify which MLS-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.
Read the scenario before looking for a memorised answer.
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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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