Automatic Discovery of Latent Clusters in General Regression Models
[Thesis]
Minhazul Islam S. K.
Banerjee, Arunava
University of Florida
2017
108
Place of publication: United States, Ann Arbor; ISBN=978-0-438-12217-8
Ph.D.
University of Florida
2017
We present a flexible nonparametric Bayesian framework for automatic detection of local clusters in general regression models. The models are built using techniques that are now considered standard in statistical parameter estimation literature, namely Dirichlet Process (DP), Hierarchical Dirichlet Process (HDP), Generalized Linear Model (GLM) and Hierarchical Generalized Linear Model (HGLM). These Bayesian nonparametric techniques have been widely applied to solve clustering problems in the real world.