BN-structure-1

BN-structure-1 - Bayesian Network Structure Learning (Part...

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Bayesian Network Structure Learning (Part 1) BMI/CS 576 www.biostat.wisc.edu/bmi576/ Mark Craven [email protected] Fall 2011 The structure learning task structure learning methods have two main components 1. a scheme for scoring a given BN structure 2. a search procedure for exploring the space of structures
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Bayes net structure learning case study [Friedman et al., JCB 2000] expression levels in populations of yeast cells 800 genes 76 experimental conditions used two representations of the data – discrete representation (underexpressed, normal, overexpressed) with CPTs in the models – continuous representation with linear Gaussians Structure search operators A B C D A B C D add an edge A B C D delete an edge A B C D reverse an edge given the current network at some stage of the search, we can…
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hill-climbing given : data set D , initial network B 0 i = 0 B best ! B 0 while stopping criteria not met { for each possible operator application a { B new ! apply( a , B i ) if score( B new ) > score( B best ) B best ! B new } ++i B i ! B best } Information theory background Before we consider the next structure learning
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This note was uploaded on 12/15/2011 for the course BMI 576 taught by Professor Staff during the Fall '11 term at Wisc Green Bay.

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BN-structure-1 - Bayesian Network Structure Learning (Part...

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