A hybrid approach to learn Bayesian networks using evolutionary programming

Document Type

Conference paper

Source Publication

Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002

Publication Date

1-1-2002

Volume

2

First Page

1314

Last Page

1319

Publisher

IEEE Computer Society

Abstract

A novel hybrid framework is reported that improves upon our previous work, MDLEP, which uses evolutionary programming to solve the difficult Bayesian network learning problem. A new merge operator is also introduced that further enhances the efficiency. As experimental results suggest, our hybrid approach performs significantly better than MDLEP.

DOI

10.1109/CEC.2002.1004433

Publisher Statement

Copyright © 2002 IEEE. Access to external full text or publisher's version may require subscription.

Additional Information

Paper presented at the IEEE World Congress on Computational Intelligence (WCCI2002), May 12-17, 2002, Honolulu, Hawaii.

ISBN of the source publication: 9780780372825

Full-text Version

Publisher’s Version

Language

English

Share

COinS