This article helped me a lot in understanding the concept.
In summary,
- Both are probabilistic models, meaning they both use probability (conditional probability , to be precise) to calculate classes for the unknown data.
- The Generative Classifiers apply Joint PDF & Bayes Theorem on the data set and calculate conditional probability using values from those.
- The Discriminative Classifiers directly find Conditional probablity on the data set
Some good reading material: conditional probability , Joint PDF