Rule Induction Using Multi-Objective Metaheuristics: Encouraging Rule Diversity

Reynolds, A. P. and de la Iglesia, B. (2006) Rule Induction Using Multi-Objective Metaheuristics: Encouraging Rule Diversity. In: 2006 IEEE World Congress on Computational Intelligence and 2006 International Joint Conference on Neural Networks, 2006-07-16 - 2006-07-21.

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Abstract

Previous research produced a multi-objective metaheuristic for partial classification, where rule dominance is determined through the comparison of rules based on just two objectives: rule confidence and coverage. The user is presented with a set of descriptions of the class of interest from which he may select a subset. This paper presents two enhancements to this algorithm, describing how the use of modified dominance relations may increase the diversity of rules presented to the user and how clustering techniques may be used to aid in the presentation of the potentially large sets of rules generated.

Item Type: Conference or Workshop Item (Paper)
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: Vishal Gautam
Date Deposited: 01 Jun 2011 19:32
Last Modified: 28 Oct 2019 15:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/22071
DOI: 10.1109/IJCNN.2006.247333

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