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JMLR
2010

Dirichlet Process Mixtures of Generalized Linear Models

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Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models a response variable locally by a generalized linear model. We give conditions for the existence and asymptotic unbiasedness of the DP-GLM regression mean function estimate; we then give a practical example for when those conditions hold. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression including regression trees and Gaussian processes.
Lauren Hannah, David M. Blei, Warren B. Powell
Added 19 May 2011
Updated 19 May 2011
Type Journal
Year 2010
Where JMLR
Authors Lauren Hannah, David M. Blei, Warren B. Powell
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