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 | |
| 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: 9780780372825Fingerprint
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