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AI0-001 AI Concepts and Foundations Practice Question

A marketing team wants to segment customers into groups based on purchasing behavior without predefined categories. Which algorithm should they use?

⚠ Common exam trap

CompTIA often tests the distinction between supervised and unsupervised learning, and the trap here is that candidates may confuse clustering (unsupervised) with classification (supervised) algorithms, leading them to pick a classifier like Naive Bayes or logistic regression instead of K-means.

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

K-means clustering

K-means clustering is an unsupervised learning algorithm that groups data points into clusters based on similarity without requiring predefined labels. Since the marketing team wants to segment customers based on purchasing behavior without predefined categories, K-means is the correct choice as it discovers natural groupings in the data.

Answer analysis

Option-by-option breakdown

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

  • K-means clustering

    Why this is correct

    K-means is an unsupervised algorithm that groups data into clusters based on similarity, perfect for segmentation.

  • Naive Bayes classifier

    Why it's wrong here

    Naive Bayes is a probabilistic classifier requiring labeled data, not suitable for unsupervised tasks.

  • Logistic regression

    Why it's wrong here

    Logistic regression is a supervised classification algorithm requiring labeled data, not suitable for unsupervised segmentation.

  • Support vector machine

    Why it's wrong here

    SVM is a supervised learning algorithm for classification or regression, not for unsupervised clustering.

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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.