Testing Significance in Bayesian Classifiers.

Frontiers in Artificial Intelligence and Applications 132:34-41 (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.

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Julio Michael Stern
University of São Paulo

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