A team is building a spam detection system.

→ Naive Bayes is a probabilistic classification algorithm based on Bayes’ theorem. It is lightweight, fast, and effective for text-based classification problems like spam detection. It also performs well with small or simple training sets.

Why the other options are incorrect:

A: Logistic regression is also probabilistic but requires more feature preprocessing.

B: Random forest is accurate but computationally heavier.

D: Linear regression is for continuous targets — not suitable for classification.

Official References:

CompTIA DataX (DY0-001) Study Guide – Section 4.1:“Naive Bayes classifiers are ideal for spam detection and similar applications due to their efficiency and probabilistic nature.”

Text Classification Techniques, Chapter 4:“Naive Bayes requires minimal training and works well with high-dimensional, sparse data such as email content.”