Approximate Bayesian networks

Authors:
Dominik Ślȩzak
Affiliations:
Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warsaw, Poland and Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warsaw, Poland
Venue:
Technologies for constructing intelligent systems
Year:
2002

Citing 12
Cited 4

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Probabilistic reasoning in intelligent systems: networks of plausible inference
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Information Theory and Reliable Communication

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Normalized Decision Functions and Measures for Inconsistent Decision Tables Analysis

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Abstract

We introduce the notion of an approximate Bayesian network, which almost keeps the information entropy of data and encodes knowledge about approximate dependencies between features. Presented theoretical results, as well as relationships to fundamental concepts of the rough set theory, provide a novel methodology of applying the Bayesian net models to the real life data analysis.