Diversity Measures for Building Multiple Classifier Systems Using Genetic Algorithms

Authors

  • Leidys Cabrera Hernández Universidad Central “Marta Abreu” de Las Villas (UCLV), Departamento de Computación, Centro de Estudios de Informática (CEI), Facultad de Matemáticas, Física y Computación (MFC)
  • Alejandro Morales Hernández Universidad Central “Marta Abreu” de Las Villas (UCLV), Departamento de Computación, Centro de Estudios de Informática (CEI), Facultad de Matemáticas, Física y Computación (MFC)
  • Gladys María Casas Cardoso Universidad Central “Marta Abreu” de Las Villas (UCLV), Departamento de Computación, Centro de Estudios de Informática (CEI), Facultad de Matemáticas, Física y Computación (MFC)

DOI:

https://doi.org/10.13053/cys-20-4-2513

Keywords:

Diversity measures, multi-classifier, classifiers, genetic algorithms.

Abstract

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 forbuilding 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.

Author Biographies

Leidys Cabrera Hernández, Universidad Central “Marta Abreu” de Las Villas (UCLV), Departamento de Computación, Centro de Estudios de Informática (CEI), Facultad de Matemáticas, Física y Computación (MFC)

Es Master en Bioinformática y Biología Computacional, 2013, en la Universidad Central “Marta Abreu” de Las Villas (UCLV), Cuba. Licenciada en Ciencias de la Computación, 2009. Profesora de la UCLV en la facultad de Computación e Investigadora del Laboratorio de Bioinformática del Centro de Estudios Informáticos. Áreas de interés: Bioinformática y Sistemas Multiclasificadores.

Alejandro Morales Hernández, Universidad Central “Marta Abreu” de Las Villas (UCLV), Departamento de Computación, Centro de Estudios de Informática (CEI), Facultad de Matemáticas, Física y Computación (MFC)

Es Licenciado en Ciencias de la Computación, 2014, de la Universidad Central “Marta Abreu” de Las Villas (UCLV), Cuba. Investigador del XETID, Empresa de Tecnologías de la Información (UCLV). Áreas de interés: Sistemas Multiclasificadores.

Gladys María Casas Cardoso, Universidad Central “Marta Abreu” de Las Villas (UCLV), Departamento de Computación, Centro de Estudios de Informática (CEI), Facultad de Matemáticas, Física y Computación (MFC)

Es Licenciada en Cibernética Matemática (1994), Master en Matemática (1998), Doctora en Ciencias Técnicas (2004) en la Universidad Central “Marta Abreu” de Las Villas (UCLV), Cuba. Profesora de la UCLV en la facultad de Matemática, Física y Computación e Investigadora del Laboratorio de Bioinformática del Centro de Estudios Informáticos. Áreas de interés: Bioinformática, Estadística Computacional y Sistemas Multi-clasificadores.

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Published

2016-12-18

Issue

Vol. 20 No. 4 (2016): Thematic Issue: Research Advances and Applications of Evolutionary Computation (Guest Editors: H.J. Escalante, M. Graff)

Section

Articles

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