This document outlines Bayesian scoring functions that are used to score Bayesian belief networks (BBNs). It defines BBNs and covers the probability distributions and mathematical concepts that Bayesian scoring functions are based on, such as the multinomial and Dirichlet distributions. The document then provides examples of several Bayesian scoring functions, including the Bayesian Dirichlet scoring function, K2 scoring function, and BDe and BDeu scoring functions.
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Bayesian scoring functions for Bayesian Belief Networks
2. PURPOSE AND OUTLINE
? Purpose: concisely illustrate how some Bayesian scoring
functions have been established to score Bayesian belief
networks (BBNs)
? Define a BBN
? Cover what Bayesian scoring functions are based on
? Basic mathematic functions (factorial, gamma, and Beta functions)
? Probability distributions (multinomial, Dirichlet, Dirichlet-multinomial)
? Bayes Theorem
? Assumptions
? Give a few Bayesian scoring function examples (BD, K2, BDe,
BDeu)
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3. DEFINITION OF A BBN
? ?
A BBN is defined as a pair (G,P) where G and P themselves are defined as follows
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