AI0-001 AI Governance and Ethics Practice Question
A data scientist is using LIME to explain a black-box model. Which TWO characteristics of LIME are true?
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
✓
It creates an interpretable surrogate model locally around a prediction
LIME (Local Interpretable Model-agnostic Explanations) creates local surrogate models to explain individual predictions. It does not provide global feature importance or an inherent measure of model confidence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It provides a measure of model confidence in its prediction
Why it's wrong here
LIME does not measure confidence; it only provides local explanations.
- ✗
It requires access to the model's internal parameters
Why it's wrong here
LIME only requires access to the model's prediction function, not its internals.
- ✗
It provides a global ranking of feature importance across the entire dataset
Why it's wrong here
LIME is local, not global; it explains individual predictions.
- ✓
It creates an interpretable surrogate model locally around a prediction
Why this is correct
LIME generates a simple model that approximates the black-box model near the instance being explained.
- ✓
It can be used with any machine learning model
Why this is correct
LIME is model-agnostic and works with any classifier or regressor.
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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.