A hybrid approach to learn Bayesian networks using evolutionary programming

Man Leung WONG; Shing Yan LEE; Kwong Sak LEUNG

doi:10.1109/CEC.2002.1004433

A hybrid approach to learn Bayesian networks using evolutionary programming

Man Leung WONG, Shing Yan LEE, Kwong Sak LEUNG

Department of Computing and Decision Sciences

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed)

7 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002
Publisher	IEEE Computer Society
Pages	1314-1319
Number of pages	6
Volume	2
ISBN (Print)	9780780372825
DOIs	https://doi.org/10.1109/CEC.2002.1004433
Publication status	Published - 1 Jan 2002

Bibliographical note

Paper presented at the IEEE World Congress on Computational Intelligence (WCCI2002), May 12-17, 2002, Honolulu, Hawaii. ISBN of the source publication: 9780780372825

Access to Document

10.1109/CEC.2002.1004433

DC@Lingnan

Fingerprint Dive into the research topics of 'A hybrid approach to learn Bayesian networks using evolutionary programming'. Together they form a unique fingerprint.

Cite this

WONG, M. L., LEE, S. Y., & LEUNG, K. S. (2002). A hybrid approach to learn Bayesian networks using evolutionary programming. In Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002 (Vol. 2, pp. 1314-1319). IEEE Computer Society. https://doi.org/10.1109/CEC.2002.1004433

@inproceedings{72873bf56910446c8f132882772d92ce,

title = "A hybrid approach to learn Bayesian networks using evolutionary programming",

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.",

author = "WONG, {Man Leung} and LEE, {Shing Yan} and LEUNG, {Kwong Sak}",

note = "Paper presented at the IEEE World Congress on Computational Intelligence (WCCI2002), May 12-17, 2002, Honolulu, Hawaii. ISBN of the source publication: 9780780372825",

year = "2002",

month = jan,

day = "1",

doi = "10.1109/CEC.2002.1004433",

language = "English",

isbn = "9780780372825",

volume = "2",

pages = "1314--1319",

booktitle = "Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002",

publisher = "IEEE Computer Society",

address = "United States",

}

TY - GEN

T1 - A hybrid approach to learn Bayesian networks using evolutionary programming

AU - WONG, Man Leung

AU - LEE, Shing Yan

AU - LEUNG, Kwong Sak

N1 - Paper presented at the IEEE World Congress on Computational Intelligence (WCCI2002), May 12-17, 2002, Honolulu, Hawaii. ISBN of the source publication: 9780780372825

PY - 2002/1/1

Y1 - 2002/1/1

N2 - 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.

AB - 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.

UR - http://commons.ln.edu.hk/sw_master/6858

U2 - 10.1109/CEC.2002.1004433

DO - 10.1109/CEC.2002.1004433

M3 - Conference paper (refereed)

SN - 9780780372825

VL - 2

SP - 1314

EP - 1319

BT - Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002

PB - IEEE Computer Society

ER -