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Inclusión en Weka de filtros basados en conjuntos aproximados para bases desbalanceadas (Inclusion of filters in Weka based in rough sets for imbalanced bases)

Author

Listed:
  • Addel Arnaldo Goya Jorge

    (Universidad Central “Marta Abreu” de Las Villas)

  • Deborah Galpert Cañizares

    (Universidad Central “Marta Abreu” de Las Villas)

  • Felipe Antonio Enríquez Rodríguez

    (Universidad Central “Marta Abreu” de Las Villas)

Abstract

Resumen El problema de desbalance en la clasificación se presenta en conjuntos de datos que tienen una cantidad grande de datos de cierto tipo (clase mayoritaria), mientras que el número de datos del tipo contrario es considerablemente menor (clase minoritaria). En este artículo se hace un breve resumen de la teoría de conjuntos aproximados basados en relaciones de similitud para su utilización en la implementación en Weka de tres filtros para tratar el problema de desbalance de clases. Luego se realiza un análisis de los resultados en dos conjuntos de datos para probar su validación, obteniéndose resultados satisfactorios. English abstract The class imbalance problem is shown in datasets which have a great amount of data of a certain type (majority class), whilst in the case of the contrary data type it is considerably less (minority class). In this paper, a brief summary of the rough set theory is made based in similarity relations for its use on three filters Weka for class imbalance management. Finally, an analysis of the results in both sets of data is made in order to prove its validation, obtaining satisfying results.

Suggested Citation

  • Addel Arnaldo Goya Jorge & Deborah Galpert Cañizares & Felipe Antonio Enríquez Rodríguez, 2015. "Inclusión en Weka de filtros basados en conjuntos aproximados para bases desbalanceadas (Inclusion of filters in Weka based in rough sets for imbalanced bases)," Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), vol. 3(2), pages 53-62.
    • Handle: RePEc:rge:journl:v:3:y:2015:i:2:p:53-62
    DOI: 10.5281/zenodo.7080865
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    More about this item

    Keywords

    Clasificación; Conjuntos Aproximados; Desbalance; Filtros; Classification; Rough Sets; Imbalance; Filters;
    All these keywords.

    JEL classification:

    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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