Learning Bayesian Network Structures by Searching For the Best Ordering With Genetic Algorithms (1996)
| Venue: | IEEE Transactions on Systems, Man and Cybernetics |
| Citations: | 45 - 9 self |
BibTeX
@ARTICLE{Larrañaga96learningbayesian,
author = {Pedro Larrañaga and Cindy M. H. Kuijpers and Roberto H. Murga and Yosu Yurramendi},
title = {Learning Bayesian Network Structures by Searching For the Best Ordering With Genetic Algorithms},
journal = {IEEE Transactions on Systems, Man and Cybernetics},
year = {1996},
volume = {26},
pages = {487--493}
}
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Abstract
In this paper we present a ne_(l n [!ii ' with respect to Bayesian networks con- ogy for inducing Bayesian network structures frop3 titute the roblem of the evidence propagation and a database of cases. The methodology is based oap&lll searching for the best ordering of the system vari- the problem of the model search. The problem of shies by means of genetic algorithl{. Since his th_vidence propagation consists of once the vMproblem of finding an optimal ordea. teeuarue}rables are known, the assignment of resembles the traveling salesman p'FolUleh)ve use .... IW. ....... probablhles to the values of the rest of the van genetic operators that were developed for the latter - problem. The quality of a variable ordering is eval- ables. Cooper [4] demonstrated that this problem Mated with the algorithm K2. We present empirical results that were obtained with a simulation of the ALARM network.
