Question: 29
(Choose 1 answer)
How do Support Vector Machines (SVMS) differ from Naïve Bayes classifiers in their approach to
classification problems?
A. SVMs focus on probabilistic principles, while Naïve Bayes classifiers use geometric principles
B. SVMs treat inputs as points in geometric space, while Naïve Bayes relies on textual analysis
C. Naïve Bayes classifiers aim to find geometric hyperplanes, while SVMs are purely probabilistic in nature
D. SVMs aim to find a hyperplane in a geometric space, while Naïve Bayes is purely based on probability
calculations
