An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network

J.H. Bolt; L.C. van der Gaag

An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network

J.H. Bolt
, L.C. van der Gaag

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

The use of the noisy-OR model is advocated throughout the literature as an approach to lightening the task of obtaining all probabilities required for a Bayesian network. Little evidence is available, however, as to the effects of using the model on a network's performance. In this paper, we construct a noisy-OR version of a real-life hand-built Bayesian network of moderate size, and compare the performance of the original network with that of the constructed noisy-OR version. Empirical results from using the two networks on real-life data show that the performance of the original network does not degrade by using the noisy-OR model.

Original language	English
Title of host publication	Information Processing and Management of Uncertainty in Knowledge-Based Systems
Editors	E. Huellermeier, R. Kruse, F. Hoffmann
Publisher	Springer
Pages	11-20
Number of pages	10
Publication status	Published - 2010

Cite this

@inproceedings{e0171c23d2464149872b2731c9b565e6,

title = "An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network",

abstract = "The use of the noisy-OR model is advocated throughout the literature as an approach to lightening the task of obtaining all probabilities required for a Bayesian network. Little evidence is available, however, as to the effects of using the model on a network's performance. In this paper, we construct a noisy-OR version of a real-life hand-built Bayesian network of moderate size, and compare the performance of the original network with that of the constructed noisy-OR version. Empirical results from using the two networks on real-life data show that the performance of the original network does not degrade by using the noisy-OR model.",

author = "J.H. Bolt and \{van der Gaag\}, L.C.",

year = "2010",

language = "English",

pages = "11--20",

editor = "E. Huellermeier and R. Kruse and F. Hoffmann",

booktitle = "Information Processing and Management of Uncertainty in Knowledge-Based Systems",

publisher = "Springer",

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An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network. / Bolt, J.H.; van der Gaag, L.C.
Information Processing and Management of Uncertainty in Knowledge-Based Systems. ed. / E. Huellermeier; R. Kruse; F. Hoffmann. Springer, 2010. p. 11-20.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network

AU - Bolt, J.H.

AU - van der Gaag, L.C.

PY - 2010

Y1 - 2010

N2 - The use of the noisy-OR model is advocated throughout the literature as an approach to lightening the task of obtaining all probabilities required for a Bayesian network. Little evidence is available, however, as to the effects of using the model on a network's performance. In this paper, we construct a noisy-OR version of a real-life hand-built Bayesian network of moderate size, and compare the performance of the original network with that of the constructed noisy-OR version. Empirical results from using the two networks on real-life data show that the performance of the original network does not degrade by using the noisy-OR model.

AB - The use of the noisy-OR model is advocated throughout the literature as an approach to lightening the task of obtaining all probabilities required for a Bayesian network. Little evidence is available, however, as to the effects of using the model on a network's performance. In this paper, we construct a noisy-OR version of a real-life hand-built Bayesian network of moderate size, and compare the performance of the original network with that of the constructed noisy-OR version. Empirical results from using the two networks on real-life data show that the performance of the original network does not degrade by using the noisy-OR model.

M3 - Conference contribution

SP - 11

EP - 20

BT - Information Processing and Management of Uncertainty in Knowledge-Based Systems

A2 - Huellermeier, E.

A2 - Kruse, R.

A2 - Hoffmann, F.

PB - Springer

ER -

An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network

Abstract

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