AI0-001 Machine Learning and Deep Learning Practice Question
Which TWO techniques are commonly used to handle missing data in a machine learning dataset? (Choose TWO.)
⚠ Common exam trap
CompTIA often tests the distinction between data preprocessing techniques (like normalization and encoding) and actual missing data handling methods, so candidates mistakenly select normalization or one-hot encoding as solutions for missing values.
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
✓
Imputation with mean or median
Imputation with mean or median is a standard technique for handling missing numerical data because it preserves the dataset size and avoids introducing bias from simply discarding rows. By replacing missing values with the central tendency of the observed data, the model can still learn patterns without losing information, though it may reduce variance slightly.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Normalization
Why it's wrong here
Normalization scales features to a range, not for missing data.
- ✓
Imputation with mean or median
Why this is correct
Replacing missing values with mean/median is a common imputation method.
- ✓
Deletion of rows with missing values
Why this is correct
Removing rows with missing data is a straightforward approach when the missing rate is low.
- ✗
One-hot encoding
Why it's wrong here
One-hot encoding converts categorical variables to binary, not a missing data technique.
- ✗
Dimensionality reduction
Why it's wrong here
Dimensionality reduction reduces number of features, not for missing data.
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.