Discriminative Learning

Definition

Discriminative learning refers to any classification learning process that classifies by using a model or estimate of the probability P(y | x) without reference to an explicit estimate of any of P(x ), P(y, x), or P(x | y), where y is a class and x is a description of an object to be classified. Discriminative learning contrasts to generative learning which classifies by using an estimate of the joint probability P(y, x) or of the prior probability P(y) and the conditional probability P(x | y).

It is also common to categorize as discriminative any approaches that are directly based on a decision risk function (such as Support Vector Machines, Artificial Neural Networks, and Decision Trees), where the decision risk is minimized without estimation of P(x ), P(y, x), or P(x | y).

Cross-References

• Generative and Discriminative Learning