DA0-002 Data Analysis Practice Question
A data scientist is working with a dataset containing 1000 features and 500 samples. The goal is to build a predictive model. Which technique should be used to reduce the number of features while retaining most of the variance?
⚠ Common exam trap
CompTIA often tests the distinction between supervised feature selection (Lasso, Forward selection) and unsupervised dimensionality reduction (PCA), trapping candidates who confuse regularization with variance-based reduction.
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
✓
Principal Component Analysis (PCA)
Principal Component Analysis (PCA) is an unsupervised dimensionality reduction technique that transforms the original features into a set of orthogonal components, ordered by the variance they capture. Given 1000 features and only 500 samples, PCA is ideal because it reduces the feature space while retaining the maximum variance, helping to avoid overfitting and the curse of dimensionality.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ridge regression
Why it's wrong here
Ridge does not reduce features; it shrinks coefficients.
- ✗
Forward selection
Why it's wrong here
Forward selection is a feature selection method but may not capture variance optimally.
- ✓
Principal Component Analysis (PCA)
Why this is correct
PCA reduces dimensionality by creating new features that capture maximum variance.
- ✗
Lasso regression
Why it's wrong here
Lasso performs feature selection but is supervised and may not retain variance.
Go deeper
Related to this question
About these practice questions
This DA0-002 question is part of Courseiva's 986-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 DA0-002 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 DA0-002 exam.