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de la Iglesia, B. 
ORCID: https://orcid.org/0000-0003-2675-5826 and Reynolds, A. P.
(2005)
The use of meta-heuristic algorithms for data mining.
In: 1st International Conference on Information and Communication Technologies, 2005-08-27 - 2005-08-28.
Abstract
In this paper we explore the application of powerful optimisers known as metaheuristic algorithms to problems within the data mining domain. We introduce some well-known data mining problems, and show how they can be formulated as optimisation problems. We then review the use of metaheuristics in this context. In particular, we focus on the task of partial classification and show how multi-objective metaheuristics have produced results that are comparable to the best known techniques but more scalable to large databases. We conclude by reinforcing the importance of research on the areas of metaheuristics for optimisation and data mining. The combination of robust methods for solving real-life problems in a reasonable time and the ability to apply these methods to the analysis of large repositories of data may hold the key for success in many other scientific and commercial application areas.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Keynote address |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Medicine and Health Sciences > Research Centres > Business and Local Government Data Research Centre (former - to 2023) Faculty of Science > Research Groups > Data Science and Statistics Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre |
| Depositing User: | Vishal Gautam |
| Date Deposited: | 14 Jun 2011 15:33 |
| Last Modified: | 22 Apr 2023 02:45 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/23537 |
| DOI: | 10.1109/ICICT.2005.1598541 |
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