FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms
AbstractVarious 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Omega.
Volume (Year): 39 (2011)
Issue (Month): 6 (December)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- 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.
- 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.
- 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.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.