Testing Significance in Bayesian Classifiers

  • Authors:

  • Marcelo de S. Lauretto;Julio M. Stern

  • Affiliations:

  • BIOINFO and Computer Science Dept., São Paulo University;BIOINFO and Computer Science Dept., São Paulo University

  • Venue:
  • Proceedings of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005
  • Year:
  • 2005

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Abstract

The Fully Bayesian Significance Test (FBST) is a coherent Bayesian significance test for sharp hypotheses. This paper explores the FBST as a model selection tool for general mixture models, and gives some computational experiments for Multinomial-Dirichlet-Normal-Wishart models.