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Generative vs Discriminative Models (Naive Bayes)
A discriminative model learns P(y|x) directly, the decision boundary. A generative model learns the joint P(x,y), so it models how the data is produced and recovers the label via Bayes. Naive Bayes is the canonical generative classifier and rests on a strong conditional-independence assumption. AI, ML, and GenAI engineer interviews probe this to check whether you know that generative wins with little data or missing features while discriminative wins on raw accuracy once data is plentiful.
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