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Author Kontkanen, Petri ♦ Myllymäki, Petri ♦ Silander, Tomi ♦ Tirri, Henry
Source CiteSeerX
Content type Text
Publisher Morgan Kaufmann Publishers
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Bayesian Network ♦ Bayesian Network Structure ♦ Prediction Task ♦ Priori Known ♦ Supervised Selection ♦ Supervised Model Selection ♦ Supervised Bayesian Network Selection Task ♦ Marginal Likelihood Score ♦ Joint Probability Distribution ♦ Supervised Domain ♦ Standard Marginal Likelihood Score ♦ Possible Model ♦ Focused Predictive Distribution ♦ Predictive Distribution ♦ Unsupervised Sense ♦ Unsupervised Task ♦ Domain Joint Probability Distribution ♦ Chosen Model ♦ Data Sample ♦ Accurate Model ♦ Unsupervised Model Selection Problem
Description Given a set of possible models (e.g., Bayesian network structures) and a data sample, in the unsupervised model selection problem the task is to choose the most accurate model with respect to the domain joint probability distribution. In contrast to this, in supervised model selection it is a priori known that the chosen model will be used in the future for prediction tasks involving more "focused" predictive distributions. Although focused predictive distributions can be produced from the joint probability distribution by marginalization, in practice the best model in the unsupervised sense does not necessarily perform well in supervised domains. In particular, the standard marginal likelihood score is a criterion for the unsupervised task, and, although frequently used for supervised model selection also, does not perform well in such tasks. In this paper we study the performance of the marginal likelihood score empirically in supervised Bayesian network selection tasks by using a la...
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 1999-01-01
Publisher Institution In UAI99