CompTIA DataX (DY0-001) — Question 58

A team is building a spam detection system. The team wants a probability-based identification method without complex, in-depth training from the historical data set. Which of the following methods would best serve this purpose?

Answer options

• A. Logistic regression
• B. Random forest
• C. Naive Bayes
• D. Linear regression

Correct answer: C

Explanation

Naive Bayes is ideal for spam detection because it operates on the principle of probabilities and assumes independence between features, allowing it to function effectively without extensive training. In contrast, Logistic regression and Linear regression are more suited for different types of predictions, while Random forest, despite being powerful, involves more complexity and deeper training, which the team wishes to avoid.