Data Mining - Generative Model


Generative model

Generative models are typically more flexible than discriminative models in expressing dependencies in complex learning tasks.

Generative model returns probabilities.

Generative model is a full probabilistic model of all variables, whereas a discriminative model provides a model only for the target variable(s) conditional on the observed variables. Thus a generative model can be used, for example, to simulate (i.e. generate) values of any variable in the model, whereas a discriminative model allows only sampling of the target variables conditional on the observed quantities.


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