Sciweavers

Share
ECML
2005
Springer

On Discriminative Joint Density Modeling

9 years 2 months ago
On Discriminative Joint Density Modeling
Abstract. We study discriminative joint density models, that is, generative models for the joint density p(c, x) learned by maximizing a discriminative cost function, the conditional likelihood. We use the framework to derive generative models for generalized linear models, including logistic regression, linear discriminant analysis, and discriminative mixture of unigrams. The benefits of deriving the discriminative models from joint density models are that it is easy to extend the models and interpret the results, and missing data can be treated using justified standard methods.
Jarkko Salojärvi, Kai Puolamäki, Samuel
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ECML
Authors Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski
Comments (0)
books