The use of meta-heuristic algorithms for data mining

B. de la Iglesia, A. P. Reynolds

Research output: Contribution to conferencePaper

2 Citations (Scopus)

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.
Original languageEnglish
Pages34-44
Number of pages11
DOIs
Publication statusPublished - Aug 2005
EventProceedings of the First International Conference on Information and Communication Technologies, Keynote Address -
Duration: 27 Aug 200528 Aug 2005

Conference

ConferenceProceedings of the First International Conference on Information and Communication Technologies, Keynote Address
Period27/08/0528/08/05

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