Courseiva
ModelingeasyMultiple ChoiceObjective-mapped

MLS-C01 Modeling Practice Question

A machine learning team is developing a model to predict housing prices. They have a dataset with numerical features like square footage and number of bedrooms, and categorical features like neighborhood. Which preprocessing step is essential before training a linear regression model?

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

One-hot encode categorical features

One-hot encoding converts categorical features into binary columns, which linear regression requires. Option A is wrong because scaling is important but not the only essential step; encoding is needed first. Option B is wrong because removing correlated features can help with multicollinearity but is not essential for linear regression. Option D is wrong because PCA reduces dimensionality but is optional and not a preprocessing step required before training.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Normalize all numerical features to have zero mean and unit variance

    Why it's wrong here

    Scaling is important but encoding categorical variables is equally essential.

  • Remove highly correlated features

    Why it's wrong here

    Feature selection is optional and not essential for all linear regression models.

  • One-hot encode categorical features

    Why this is correct

    Linear regression requires numerical input; one-hot encoding is needed for categorical variables.

  • Apply Principal Component Analysis (PCA) to reduce dimensionality

    Why it's wrong here

    PCA is optional and not always necessary.

About these practice questions

One of 1,672 original MLS-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This MLS-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 MLS-C01 exam.