AI0-001 Recall Practice Question
Exhibit
The following is a confusion matrix for a binary classifier:
Predicted: Positive Predicted: Negative
Actual Positive: 80 20
Actual Negative: 30 70Refer to the exhibit. What is the recall of the model?
⚠ Common exam trap
CompTIA often tests recall by providing a confusion matrix and expects candidates to correctly identify the denominator as TP+FN, not total samples, to avoid confusing recall with accuracy or precision. In this question, the key is correctly reading TP=80 and FN=20 from the exhibit.
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
✓
0.8
Recall is calculated as True Positives divided by (True Positives + False Negatives). From the confusion matrix, True Positives = 80 and False Negatives = 20, so recall = 80 / (80 + 20) = 80 / 100 = 0.8. This measures the model's ability to correctly identify all actual positive cases.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
0.72
Why it's wrong here
0.72 is approximate accuracy (150/200=0.75, not 0.72).
- ✓
0.8
Why this is correct
TP=80, FN=20, recall=80/100=0.8
- ✗
0.7
Why it's wrong here
0.7 is specificity (70/100=0.7).
- ✗
0.73
Why it's wrong here
0.73 is approximate precision (80/(80+30)=0.727).
About these practice questions
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.