Serviços Personalizados
Journal
Artigo
Indicadores
Citado por SciELO
Acessos
Links relacionados
Similares em SciELO
Compartilhar
Computación y Sistemas
versão On-line ISSN 2007-9737versão impressa ISSN 1405-5546
Resumo
CABRERA-HERNANDEZ, Leidys; MORALES-HERNANDEZ, Alejandro e CASAS-CARDOSO, Gladys María. Diversity Measures for Building Multiple Classifier Systems Using Genetic Algorithms. Comp. y Sist. [online]. 2016, vol.20, n.4, pp.729-747. ISSN 2007-9737. https://doi.org/10.13053/cys-20-4-2513.
In this paper we present the different diversity measures that exist in the literature to decide if a set of classifiers is diverse, aspect that is very important in the creation of multi-classifier systems. The modeling for building multi-classifier systems using meta-heuristic of Genetic Algorithm to ensure the best possible accuracy and greater diversity among the classifiers is presented. Various forms of combination for diversity measures are also enunciated. Finally, we discuss two experiments in which the individual behaviors of diversity measures and their combinations are analyzed.
Palavras-chave : Diversity measures; multi-classifier; classifiers; genetic algorithms.