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
