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FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms

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  • Peng, Yi
  • Kou, Gang
  • Wang, Guoxun
  • Shi, Yong
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    Abstract

    Various methods and algorithms have been developed for multiclass classification problems in recent years. How to select an effective algorithm for a multiclass classification task is an important yet difficult issue. Since the multiclass algorithm selection normally involves more than one criterion, such as accuracy and computation time, the selection process can be modeled as a multiple criteria decision making (MCDM) problem. While the evaluations of algorithms provided by different MCDM methods are in agreement sometimes, there are situations where MCDM methods generate very different results. To resolve this disagreement and help decision makers pick the most suitable classifier(s), this paper proposes a fusion approach to produce a weighted compatible MCDM ranking of multiclass classification algorithms. Several multiclass datasets from different domains are used in the experimental study to test the proposed fusion approach. The results prove that MCDM methods are useful tools for evaluating multiclass classification algorithms and the fusion approach is capable of identifying a compromised solution when different MCDM methods generate conflicting rankings.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 39 (2011)
    Issue (Month): 6 (December)
    Pages: 677-689

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    Handle: RePEc:eee:jomega:v:39:y:2011:i:6:p:677-689

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    Related research

    Keywords: Multicriteria Decision making Ranking Multiclass classification TOPSIS VIKOR PROMETHEE WSM;

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    Cited by:
    1. Ergu, Daji & Kou, Gang & Peng, Yi & Shi, Yong, 2011. "A simple method to improve the consistency ratio of the pair-wise comparison matrix in ANP," European Journal of Operational Research, Elsevier, vol. 213(1), pages 246-259, August.
    2. Kou, Gang & Lin, Changsheng, 2014. "A cosine maximization method for the priority vector derivation in AHP," European Journal of Operational Research, Elsevier, vol. 235(1), pages 225-232.
    3. Morais, Danielle C. & de Almeida, Adiel Teixeira, 2012. "Group decision making on water resources based on analysis of individual rankings," Omega, Elsevier, vol. 40(1), pages 42-52, January.
    4. Verdecho, María-José & Alfaro-Saiz, Juan-Jose & Rodriguez-Rodriguez, Raul & Ortiz-Bas, Angel, 2012. "A multi-criteria approach for managing inter-enterprise collaborative relationships," Omega, Elsevier, vol. 40(3), pages 249-263.
    5. Sue-Fen Huang & Ching-Hsue Cheng, 2013. "GMADM-based attributes selection method in developing prediction model," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(6), pages 3335-3347, October.
    6. Pang, Jifang & Liang, Jiye, 2012. "Evaluation of the results of multi-attribute group decision-making with linguistic information," Omega, Elsevier, vol. 40(3), pages 294-301.

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