Abstract
In this paper, a cross-validation and early-stopping algorithm is devised for parameter updating in the Univariate Marginal Distribution Algorithm (UMDA) to reduce overftting. Our hypothesis is that the well-known problem of diversity loss in UMDA is a consequence of overfitting during the parameter estimation step at each generation. It is tested by experiments on two different optimization problems.
| Original language | English |
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| Title of host publication | Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference|Proc. Gen. Evol. Comput. Conf. |
| Publisher | Association for Computing Machinery |
| Pages | 632-633 |
| Number of pages | 1 |
| ISBN (Print) | 1595936971, 9781595936974 |
| DOIs | |
| Publication status | Published - 2007 |
| Event | 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London Duration: 1 Jul 2007 → … http://dblp.uni-trier.de/db/conf/gecco/gecco2007.html#BrankeLS07http://dblp.uni-trier.de/rec/bibtex/conf/gecco/BrankeLS07.xmlhttp://dblp.uni-trier.de/rec/bibtex/conf/gecco/BrankeLS07 |
Conference
| Conference | 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 |
|---|---|
| City | London |
| Period | 1/07/07 → … |
| Internet address |
Keywords
- Cross-validation
- Early-stopping
- Overfitting
- Univariate marginal distribution algorithm (UMDA)