Managing Population Diversity Through the Use of Weighted Objectives and Modified Dominance: An Example from Data Mining

Reynolds, A. P. and de la Iglesia, B. (2007) Managing Population Diversity Through the Use of Weighted Objectives and Modified Dominance: An Example from Data Mining. In: Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MCDM 2007), 2007-04-01 - 2007-04-05.

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Abstract

The most successful multi-objective metaheuristics, such as NSGA II and SPEA 2, usually apply a form of elitism in the search. However, there are multi-objective problems where this approach leads to a major loss of population diversity early in the search. In earlier work, the authors applied a multi-objective metaheuristic to the problem of rule induction for predictive classification, minimizing rule complexity and misclassification costs. While high quality results were obtained, this problem was found to suffer from such a loss of diversity. This paper describes the use of both linear combinations of objectives and modified dominance relations to control population diversity, producing higher quality results in shorter run times

Item Type: Conference or Workshop Item (Paper)
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: Vishal Gautam
Date Deposited: 19 May 2011 07:26
Last Modified: 28 Oct 2019 15:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/22062
DOI: 10.1109/MCDM.2007.369423

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