I was reading about the difference between discriminative and generative models, and I read that Discriminative models learn only the boundary between classes hence they are not able to to create new datapoints. The article states, if we use a generative algorithm, for instance naive bayes, we can create new data points from class “i” basically by choosing features that maximize P(X|Y=class i ). However; the point I did not understand is that could not we also do the same creating in a discriminative model.
Take logistic regression for instance, cannot we create a vector x that maximizes P(Y=i|X=x) ? Would not this x vector would be our new sample , namely did not we generated a new sample ?