PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

On Sensitivity of the MAP Bayesian Network Structure to the Equivalent Sample Size Parameter
Tomi Silander, Petri Kontkanen and Petri Myllymäki
In: UAI-2007, 19-22 Jul 2007, Vancouver, Canada.

Abstract

BDeu marginal likelihood score is a popular model selection criterion for selecting a Bayesian network structure based on sample data. This non-informative scoring criterion assigns same score for network structures that encode same independence statements. However, before applying the BDeu score, one must determine a single parameter, the equivalent sample size α. Unfortunately no generally accepted rule for determining the α parameter has been suggested. This is disturbing, since in this paper we show through a series of concrete experiments that the solution of the network structure optimization problem is highly sensitive to the chosen α parameter value. Based on these results, we are able to give explanations for how and why this phenomenon happens, and discuss ideas for solving this problem.

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EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
ID Code:3335
Deposited By:Tomi Silander
Deposited On:08 February 2008