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ToolsGuile, Geoffrey R. and Wang, Wenjia (2007) Enhancing Boosting by Feature Non-Replacement for Microarray Data Analysis. In: 2007 International Joint Conference on Neural Networks, 2007-08-12 - 2007-08-17.
Full text not available from this repository. (Request a copy)Abstract
We have investigated strategies for enhancing ensemble learning algorithms for DNA microarray data analysis. By using modified versions of AdaBoost, LogitBoost and BagBoosting we have shown that feature non-replacement provides an effective enhancement to the performance of all three algorithms, and overall, BagBoosting with feature non-replacement had the lowest error rates when used on six commonly-used cancer datasets.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Data Science and AI |
| Depositing User: | Vishal Gautam |
| Date Deposited: | 16 May 2011 17:30 |
| Last Modified: | 24 Sep 2024 07:10 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/23447 |
| DOI: | 10.1109/IJCNN.2007.4370995 |
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