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Wednesday, 20 May 2020

Natural language processing question bank 01

Differentiate between generative and discriminative models


Difference between generative and discriminative models.


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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