Discriminative model

Discriminative models are a class of models used in machine learning for modeling the dependence of an unobserved variable $$y$$ on an observed variable $$x$$. Within a statistical framework, this is done by modeling the conditional probability distribution $$P(y|x)$$, which can be used for predicting $$x$$ from $$y$$.

Discriminative models differ from generative models in that they do not allow one to generate samples from the joint distribution of $$x$$ and $$y$$.

Examples of discriminative models used in machine learning include:
 * Linear discriminant analysis
 * Support vector machines
 * Boosting
 * Conditional random fields