Title

Using evolutionary programming and minimum description length principle for data mining of Bayesian networks

Document Type

Journal article

Source Publication

IEEE Transactions on Pattern Analysis and Machine Intelligence

Publication Date

1-1-1999

Volume

21

Issue

2

First Page

174

Last Page

178

Keywords

Bayesian networks, Evolutionary computation, Genetic algorithms, Minimum description length principle, Unsupervised learning

Abstract

We have developed a new approach (MDLEP) to learning Bayesian network structures based on the Minimum Description Length (MDL) principle and Evolutionary Programming (EP). It employs a MDL metric which is founded on information theory and integrates a knowledge-guided genetic operator for the optimization in the search process.

DOI

10.1109/34.748825

Print ISSN

01628828

Publisher Statement

Copyright ©1999 IEEE. Access to external full text or publisher's version may require subscription.

Full-text Version

Publisher’s Version

Language

English

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