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Similar Prototype Methods for Class Imbalanced Data Classification

  • Yanela Rodríguez AlvarezEmail author
  • Yailé Caballero Mota
  • Yaima Filiberto Cabrera
  • Isabel García Hilarión
  • Yumilka Fernández Hernández
  • Mabel Frias Dominguez
Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 377)

Abstract

In this paper, new methods for solving imbalanced classification problems based on prototypes are proposed. Using similarity relations for the granulation of the universe, similarity classes are generated and a prototype is selected for each similarity class. Experimental results show that the performance of our methods is statistically superior to other imbalanced methods.

Keywords

Imbalanced classification Prototype selection Prototype generation Classification Similarity relations 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yanela Rodríguez Alvarez
    • 1
    Email author
  • Yailé Caballero Mota
    • 1
  • Yaima Filiberto Cabrera
    • 1
  • Isabel García Hilarión
    • 1
  • Yumilka Fernández Hernández
    • 1
  • Mabel Frias Dominguez
    • 1
  1. 1.Departamento de ComputaciónUniversidad de CamagüeyCamagüeyCuba

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