The correct answer is that the model has high precision but low recall, missing many positives. This is because a precision of 0.95 indicates that when the model predicts a positive, it is almost always correct, resulting in very few false positives; however, a recall of only 0.60 reveals that the model fails to identify 40% of all actual positive instances, producing a high number of false negatives. On the CompTIA AI+ AI0-001 exam, this question tests your ability to interpret precision and recall metrics in isolation, often using a confusion matrix or performance report exhibit. A common trap is confusing high precision with overall model strength—remember that precision and recall measure different aspects of performance, and one can be high while the other is low. To interpret precision recall effectively, always check both values: high precision plus low recall means the model is cautious but misses many positives. For a quick memory tip, think of precision as “picky but accurate” and recall as “thorough but messy”—if one is high and the other low, the model is unbalanced.
AI0-001 Machine Learning and Deep Learning Practice Question
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.
Exhibit
Refer to the exhibit.
Evaluation report:
Precision: 0.95
Recall: 0.60
F1-score: 0.73
Based on the exhibit, what does this indicate about the model?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The model has high precision but low recall, missing many positives
Option B is correct because high precision (0.95) means few false positives, but low recall (0.60) means many false negatives, so the model misses many positive instances. Options A, C, and D are incorrect: overfitting cannot be determined from these metrics alone, underfitting would likely show both low precision and recall, and balanced performance would have similar values.
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 model has balanced performance
Why it's wrong here
F1-score of 0.73 indicates imbalance between precision and recall.
✗
The model is underfitting
Why it's wrong here
Underfitting would typically yield low precision and recall.
✗
The model is overfitting
Why it's wrong here
Overfitting is not directly evident from precision and recall alone.
✓
The model has high precision but low recall, missing many positives
Why this is correct
Correct: Precision is high, recall is low, indicating the model is conservative in labeling positives.
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 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
Got this wrong? Here's your next step.
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 — This question tests Machine Learning and Deep Learning — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The model has high precision but low recall, missing many positives — Option B is correct because high precision (0.95) means few false positives, but low recall (0.60) means many false negatives, so the model misses many positive instances. Options A, C, and D are incorrect: overfitting cannot be determined from these metrics alone, underfitting would likely show both low precision and recall, and balanced performance would have similar values.
What should I do if I get this AI0-001 question wrong?
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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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
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