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A Well-behaved Algorithm for Simulating Dependence Structures of Bayesian Networks

Xiang, Yang and Miller, Tristan (1999):
A Well-behaved Algorithm for Simulating Dependence Structures of Bayesian Networks.
In: International Journal of Applied Mathematics, pp. 923-932, 1, (8), ISSN 1311-1728,
[Online-Edition: https://download.hrz.tu-darmstadt.de/media/FB20/Dekanat/Publ...],
[Article]

Abstract

Automatic generation of Bayesian network (BNs) structures (directed acyclic graphs) is an important step in experimental study of algorithms for inference in BNs and algorithms for learning BNs from data. Previously known simulation algorithms do not guarantee connectedness of generated structures or even successful genearation according to a user specification. We propose a simple, efficient and well-behaved algorithm for automatic generation of BN structures. The performance of the algorithm is demonstrated experimentally.

Item Type: Article
Erschienen: 1999
Creators: Xiang, Yang and Miller, Tristan
Title: A Well-behaved Algorithm for Simulating Dependence Structures of Bayesian Networks
Language: English
Abstract:

Automatic generation of Bayesian network (BNs) structures (directed acyclic graphs) is an important step in experimental study of algorithms for inference in BNs and algorithms for learning BNs from data. Previously known simulation algorithms do not guarantee connectedness of generated structures or even successful genearation according to a user specification. We propose a simple, efficient and well-behaved algorithm for automatic generation of BN structures. The performance of the algorithm is demonstrated experimentally.

Journal or Publication Title: International Journal of Applied Mathematics
Volume: 1
Number: 8
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
Date Deposited: 31 Dec 2016 14:29
Official URL: https://download.hrz.tu-darmstadt.de/media/FB20/Dekanat/Publ...
Identification Number: TUD-CS-1999-0010
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