Document Detail


Bayesian feature and model selection for Gaussian mixture models.
MedLine Citation:
PMID:  16724595     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of a mixture model formulation that takes into account the saliency of the features and a Bayesian approach to mixture learning that can be used to estimate the number of mixture components. The proposed learning algorithm follows the variational framework and can simultaneously optimize over the number of components, the saliency of the features, and the parameters of the mixture model. Experimental results using high-dimensional artificial and real data illustrate the effectiveness of the method.
Authors:
Constantinos Constantinopoulos; Michalis K Titsias; Aristidis Likas
Related Documents :
16531005 - Modular learning models in forecasting natural phenomena.
23637585 - Biomarker discovery by sparse canonical correlation analysis of complex clinical phenot...
15875805 - Effective gaussian mixture learning for video background subtraction.
24727115 - Pathological gambling subtypes: a comparison of treatment-seeking and non-treatment-see...
1453785 - Comparison between the more recent techniques for smoothing and derivative assessment i...
24209865 - A poroelastic model describing nutrient transport and cell stresses within a cyclically...
Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IEEE transactions on pattern analysis and machine intelligence     Volume:  28     ISSN:  0162-8828     ISO Abbreviation:  IEEE Trans Pattern Anal Mach Intell     Publication Date:  2006 Jun 
Date Detail:
Created Date:  2006-05-26     Completed Date:  2006-06-20     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  9885960     Medline TA:  IEEE Trans Pattern Anal Mach Intell     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1013-8     Citation Subset:  IM    
Affiliation:
Department of Computer Science, University of Ioannina, Ioannina GR 45110, Greece. ccostas@cs.uoi.gr
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence*
Computer Simulation
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Information Storage and Retrieval / methods*
Models, Statistical
Normal Distribution
Pattern Recognition, Automated / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Discriminant ECOC: a heuristic method for application dependent design of error correcting output co...
Next Document:  A 3D shape constraint on video.