mediumMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A machine learning engineer needs to select…
A machine learning engineer needs to select features for a regression model. The dataset contains 50 numeric features, and the target variable is continuous. The engineer wants to reduce dimensionality by selecting features that have the strongest linear relationship with the target. Which feature selection method is MOST appropriate?
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
✓
Correlation analysis
Correlation analysis (e.g., Pearson correlation) measures the linear relationship between each feature and the target. Features with high absolute correlation can be selected. Mutual information captures non-linear relationships but is more appropriate when non-linear relationships are expected. Recursive feature elimination and Lasso are valid but more computationally expensive for initial screening.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Lasso regularization
Why it's wrong here
Lasso performs feature selection during model training, but the question focuses on a data preparation step before modeling.
- ✓
Correlation analysis
Why this is correct
Correlation analysis directly measures linear correlation (e.g., Pearson's r) between each feature and the target, making it ideal for selecting linearly related features.
- ✗
Mutual information
Why it's wrong here
Mutual information captures any non-linear dependency, but the question specifies linear relationship, so correlation is more direct.
- ✗
Recursive feature elimination (RFE)
Why it's wrong here
RFE is a wrapper method that trains models iteratively, which is computationally heavy and not the simplest for initial linear screening.
Go deeper
Related to this question
About these practice questions
This MLA-C01 question is part of Courseiva's 835-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 MLA-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLA-C01 exam.