Abstract
This paper describes the application of a multiobjective GRASP to rule selection, where previously generated simple rules are combined to give rule sets that minimize complexity and misclassfication cost. As rule selection performance depends heavily on the diversity and quality of the previously generated rules, this paper also investigates a range of multiobjective approaches for creating this initial rule set and the effect on the quality of the resulting classifier. Copyright 2009 ACM.
Original language | English |
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Title of host publication | Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 |
Pages | 643-650 |
Number of pages | 8 |
DOIs | |
Publication status | Published - 2009 |
Event | 11th Annual Genetic and Evolutionary Computation Conference 2009 - Montreal, Canada Duration: 8 Jul 2009 → 12 Jul 2009 |
Conference
Conference | 11th Annual Genetic and Evolutionary Computation Conference 2009 |
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Abbreviated title | GECCO 2009 |
Country/Territory | Canada |
City | Montreal |
Period | 8/07/09 → 12/07/09 |
Keywords
- Data mining
- GRASP
- Multiobjective optimization
- Rule induction
- Rule selection