AI0-001 AI Models and Data Engineering Practice Question
A deep learning model for image classification is overfitting due to a small dataset. The team decides to apply data augmentation. Which augmentation technique is least likely to preserve the label?
⚠ Common exam trap
CompTIA often tests the misconception that all augmentations are equally label-preserving, but the trap here is that random cropping can alter the semantic content by removing the object, while other transformations like rotation or flipping maintain the object's presence and identity.
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
✓
Random cropping and rescaling
Random cropping and rescaling is least likely to preserve the label because it can cut out the primary object or distort its proportions, potentially removing the discriminative features needed for correct classification. For example, cropping a dog image to show only the background or a leg could change the semantic meaning, making the label 'dog' incorrect. In contrast, other techniques like noise, rotation, or flipping typically retain the core subject and its label.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Adding random noise
Why it's wrong here
Noise may degrade quality but typically does not change the object class.
- ✗
Random rotation
Why it's wrong here
Rotation usually preserves the object's identity unless it's orientation-sensitive (e.g., digits).
- ✓
Random cropping and rescaling
Why this is correct
Cropping might remove the object of interest, rendering the label invalid.
- ✗
Horizontal flip
Why it's wrong here
Horizontal flip is symmetric for many objects and preserves label.
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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.