This AIF-C01 practice question tests your understanding of aif-c01 exam topics. 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 deploying a machine learning model to detect fraudulent transactions. The dataset is highly imbalanced (1% fraud). The team needs to evaluate model performance and minimize false positives while maintaining high recall. Which TWO metrics should they focus on? (Select TWO.)
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Accuracy
Why wrong: Accuracy can be misleadingly high due to class imbalance.
Recall
Recall ensures high capture of fraud cases.
Precision
Precision minimizes false positives.
F1 score
Why wrong: F1 is a combination, but the question asks for two individual metrics.
AUC-ROC
Why wrong: AUC-ROC is useful overall but does not directly focus on false positives or recall.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Recall
Precision measures how many of the predicted fraud cases are actually fraud (minimizing false positives). Recall measures how many actual fraud cases are caught. F1 balances both, but the question specifies minimizing false positives while maintaining high recall, so both precision and recall are directly relevant. AUC-ROC and accuracy are less useful for imbalanced datasets.
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.
Accuracy
Why it's wrong here
Accuracy can be misleadingly high due to class imbalance.
Recall
Why this is correct
Recall ensures high capture of fraud cases.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Precision
Why this is correct
Precision minimizes false positives.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
F1 score
Why it's wrong here
F1 is a combination, but the question asks for two individual metrics.
AUC-ROC
Why it's wrong here
AUC-ROC is useful overall but does not directly focus on false positives or recall.
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 AIF-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
Read the scenario before looking for a memorised answer.
The correct answer is: Recall — Precision measures how many of the predicted fraud cases are actually fraud (minimizing false positives). Recall measures how many actual fraud cases are caught. F1 balances both, but the question specifies minimizing false positives while maintaining high recall, so both precision and recall are directly relevant. AUC-ROC and accuracy are less useful for imbalanced datasets.
Identify which AIF-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.
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This AIF-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 AIF-C01 exam.
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