AI0-001 AI Concepts and Techniques Practice Question
A data scientist is building a model to predict whether a loan application will default. The dataset has 10,000 labeled examples with 1,000 defaults. Which metric is MOST appropriate for evaluating this highly imbalanced binary classification?
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
✓
AUC-ROC
AUC-ROC is robust to class imbalance because it measures the trade-off between true positive rate and false positive rate across all thresholds. Accuracy is misleading when classes are imbalanced. Precision and recall focus on one class but are threshold-dependent.
Answer analysis
Option-by-option breakdown
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 only considers the correctness of positive predictions, ignoring false negatives.
- ✓
AUC-ROC
Why this is correct
AUC-ROC evaluates model performance across all thresholds and is insensitive to class imbalance.
- ✗
Recall
Why it's wrong here
Recall only measures how many actual positives are captured, ignoring false positives.
- ✗
Accuracy
Why it's wrong here
Accuracy can be high even if the model predicts 'no default' for all cases, which fails to capture the minority class.
About these practice questions
This AI0-001 question is part of Courseiva's 754-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.