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A Study of Different Families of Fusion Functions for Combining Classifiers in the One-vs-One Strategy

  • Mikel Uriz
  • Daniel PaternainEmail author
  • Aranzazu Jurio
  • Humberto Bustince
  • Mikel Galar
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 854)

Abstract

In this work we study the usage of different families of fusion functions for combining classifiers in a multiple classifier system of One-vs-One (OVO) classifiers. OVO is a decomposition strategy used to deal with multi-class classification problems, where the original multi-class problem is divided into as many problems as pair of classes. In a multiple classifier system, classifiers coming from different paradigms such as support vector machines, rule induction algorithms or decision trees are combined. In the literature, several works have addressed the usage of classifier selection methods for these kinds of systems, where the best classifier for each pair of classes is selected. In this work, we look at the problem from a different perspective aiming at analyzing the behavior of different families of fusion functions to combine the classifiers. In fact, a multiple classifier system of OVO classifiers can be seen as a multi-expert decision making problem. In this context, for the fusion functions depending on weights or fuzzy measures, we propose to obtain these parameters from data. Backed-up by a thorough experimental analysis we show that the fusion function to be considered is a key factor in the system. Moreover, those based on weights or fuzzy measures can allow one to better model the aggregation problem.

Keywords

Aggregations Fusion functions Classification One-vs-One Multiple classifier system 

Notes

Acknowledgments

This work was supported in part by the Spanish Ministry of Science and Technology under Project TIN2016-77356-P (AEI/FEDER, UE).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Mikel Uriz
    • 1
  • Daniel Paternain
    • 1
    Email author
  • Aranzazu Jurio
    • 1
  • Humberto Bustince
    • 1
  • Mikel Galar
    • 1
  1. 1.Dpto. de Automática y ComputaciónUniversidad Publica de NavarraPamplonaSpain

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