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

Submitted by fjpr0013 on Wed, 24/04/2019 - 08:44
TitleOn the Use of Bagging, Mutual Information-Based Feature Selection and Multicriteria Genetic Algorithms to Design Fuzzy Rule-Based Classification Ensembles
Publication TypeConference Paper
Year of Publication2008
AuthorsCordón, O., Quirin A., and Sánchez L.
Conference Name2008 Eighth International Conference on Hybrid Intelligent Systems
Pagination549-554
Date PublishedSep.
KeywordsBagging, 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
Abstract

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.
DOI10.1109/HIS.2008.147