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