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*Differentiate between generative and discriminative models*

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__Question:__

### Difference between generative and discriminative models.

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__Answer:__

*Generative and discriminative models are probability models.*

*In*__generative model__, we model the conditional probability of the input x given the label y.

*Generative model learns the joint probability distribution P(x, y) and uses Bayes’ theorem to find the conditional probability.*

*In*__discriminative model__, we directly model the conditional probability P(y|x).

- Generative models estimate joint distribution but discriminative models estimate conditional distribution.

- In generative models, dependence assumption has to be specified for P(w|t) and P(t) but in discriminative models, arbitrary features can be incorporated for modeling P(t|w).

- Generate models can be used in unsupervised learning but discriminative models require labeled data, suitable for (semi-) supervised learning.

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