intuition behind the difference between likelihood function of discriminative and generative algorithms
Discriminative model learn to classify an x into class y: the conditional probability distribution p(y|x).

Generative models learn the joint probability distribution p(x,y).It can be transformed into p(y|x) by a Bayes rule.

You get different likelihood functions because the way those models classify data is different.