On the Use of Bagging, Mutual Information-Based Feature Selection and Multicriteria Genetic Algorithms to Design Fuzzy Rule-Based Classification Ensembles

Comunicación en congreso 2008

Autores: Óscar Cordón García, A. Quirin, L. Sánchez

Páginas 549-554

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Cómo citar esta publicación

Cordón García, Ó., Quirin, A., & Sánchez, L. (2008). On the Use of Bagging, Mutual Information-Based Feature Selection and Multicriteria Genetic Algorithms to Design Fuzzy Rule-Based Classification Ensembles. 549-554. https://doi.org/10.1109/HIS.2008.147

BibTeX

Resumen

In this contribution we explore the combination of bagging with random subspace and two variants of Battiti s mutual information feature selection methods to design fuzzy rule-based classification system ensembles. Besides, we consider a multicriteria genetic algorithm guided by the training error to select the component classifiers, in order to look for appropriate accuracy-complexity trade-offs in the final multiclassifier.

Palabras clave

Bagging
classification
Classification algorithms
fuzzy rule-based classification ensembles
fuzzy set theory
Gallium
genetic algorithms
Glass
multicriteria genetic algorithms
mutual information-based feature selection
Sonar
Training
Vehicles

Detalles

DOI: 10.1109/HIS.2008.147
Date Published: Sep.