A Rule Learning Multiobjective Particle Swarm Optimization

Multiobjective Metaheuristics (MOMH) permit to conceive a complete novel approach to induce classifiers. In the Rule Learning problem, the use of MOMH permit that the properties of the rules can be expressed in different objectives, and then the algorithm finds these rules in an unique run by explor...

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Bibliographic Details
Published inRevista IEEE América Latina Vol. 7; no. 4; pp. 478 - 486
Main Authors de Carvalho, A.B., Pozo, A.
Format Journal Article
LanguageEnglish
Published IEEE 01.08.2009
Subjects
Algorithm design and analysis
Approximation algorithms
Multiobjective Optimization
Particle swarm optimization
Rule learning
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Summary:Multiobjective Metaheuristics (MOMH) permit to conceive a complete novel approach to induce classifiers. In the Rule Learning problem, the use of MOMH permit that the properties of the rules can be expressed in different objectives, and then the algorithm finds these rules in an unique run by exploring Pareto dominance concepts. This work describes a Multiobjective Particle Swarm Optimization (MOPSO) algorithm that handles with numerical and discrete attributes. The algorithm is evaluated by using the area under ROC curve and the approximation sets produced by the algorithm are also analyzed following Multiobjective methodology.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2009.5349048