Answer / Rajeev Kumar Ranjan

Generative models learn the joint probability distribution of input variables (x) and output variables (y), while discriminative models learn the conditional probability distribution P(y|x). Generative models can generate new, synthetic data samples, but they might be less accurate in classification tasks. Discriminative models are typically more suitable for classification problems as they focus specifically on finding patterns that separate classes.

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