Generative Learning

Definition

Generative learning refers alternatively to any classification learning process that classifies by using an estimate of the joint probability P(y, x) or to any classification learning process that classifies by using estimates of the prior probability P(y) and the conditional probability P(x $\vert \,y$), where y is a class and x is a description of an object to be classified. Given such models or estimates it is possible to generate synthetic objects from the joint distribution. Generative learning contrasts to discriminative learning in which a model or estimate of P($y\,\vert$ x) is formed without reference to an explicit estimate of any of P(x), P(y, x), or P(x $\vert \,y$).

Cross References

Generative and Discriminative Learning