Quick Answer
The answer is recall. In imbalanced classification, where legitimate transactions vastly outnumber fraudulent ones, a model can achieve high accuracy by simply predicting the majority class, but recall specifically measures the proportion of actual frauds correctly identified. This metric is critical because failing to detect fraud carries far greater cost than false alarms, and recall directly quantifies the model’s ability to capture those rare positive cases. On the CompTIA AI+ AI0-001 exam, this scenario tests your understanding of why accuracy is misleading for imbalanced datasets and how recall becomes the primary metric when missing positives is unacceptable. A common trap is choosing precision, which focuses on how many flagged cases are actually fraud, but recall prioritizes catching all frauds even at the expense of some false positives. For a quick memory tip: think of recall as “recalling all the bad guys from a lineup”—you want to catch every fraudster, not just be sure the ones you catch are guilty.
This AI0-001 practice question tests your understanding of machine learning and deep learning. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 a neural network for fraud detection. The dataset has 99% legitimate, 1% fraudulent. The model achieves 99% accuracy but fails to detect most frauds. Which metric should they focus on?
Precision
Why wrong: Precision focuses on false positives, but the main issue is missing actual frauds.
F1-score
Why wrong: F1-score balances precision and recall, but recall is the primary concern.
Recall
Correct: Recall measures the proportion of actual frauds that are correctly identified.
AUC-ROC
Why wrong: AUC-ROC is a general measure but does not directly address the failure to detect frauds.
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
Option B is correct because recall measures the ability to find all positive samples (frauds), which is critical in fraud detection. Options A, C, and D are incorrect: precision is important but not as crucial as recall in this imbalanced scenario, F1-score balances precision and recall but recall directly addresses the issue, and AUC-ROC is not as intuitive for this specific problem.
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.
Precision
Why it's wrong here
Precision focuses on false positives, but the main issue is missing actual frauds.
F1-score
Why it's wrong here
F1-score balances precision and recall, but recall is the primary concern.
Recall
Why this is correct
Correct: Recall measures the proportion of actual frauds that are correctly identified.
Related concept
Read the scenario before looking for a memorised answer.
AUC-ROC
Why it's wrong here
AUC-ROC is a general measure but does not directly address the failure to detect frauds.
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 practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Identify which AI0-001 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.
Machine Learning and Deep Learning — study guide chapter
Learn the concepts, then practise the questions
Machine Learning and Deep Learning practice questions
Targeted practice on this topic area only
All AI0-001 questions
500 questions across all exam domains
CompTIA AI+ AI0-001 study guide
Full concept coverage aligned to exam objectives
AI0-001 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise AI0-001 questions linked to AI Concepts and Foundations.
Practise AI0-001 questions linked to Machine Learning and Deep Learning.
Practise AI0-001 questions linked to AI Models and Data Engineering.
Practise AI0-001 questions linked to AI Implementation and Operations.
Practise AI0-001 questions linked to AI Security, Ethics and Governance.
Practise AI0-001 questions linked to CompTIA A+ hardware.
Practise AI0-001 questions linked to CompTIA A+ mobile devices.
Practise AI0-001 questions linked to CompTIA A+ networking.
Practise AI0-001 questions linked to CompTIA A+ operating systems.
Practise AI0-001 questions linked to CompTIA A+ security.
Practise AI0-001 questions linked to CompTIA A+ software troubleshooting questions.
Practise AI0-001 questions linked to CompTIA A+ operational procedures questions.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Machine Learning and Deep Learning — This question tests Machine Learning and Deep Learning — Read the scenario before looking for a memorised answer..
The correct answer is: Recall — Option B is correct because recall measures the ability to find all positive samples (frauds), which is critical in fraud detection. Options A, C, and D are incorrect: precision is important but not as crucial as recall in this imbalanced scenario, F1-score balances precision and recall but recall directly addresses the issue, and AUC-ROC is not as intuitive for this specific problem.
Identify which AI0-001 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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 23, 2026
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.