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Decision-Making Support for the Evaluation of Clustering Algorithms Based on MCDM
Joint Authors
Kou, Gang
Xu, Zeshui
Wu, Wenshuai
Shi, Yong
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-05
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
In many disciplines, the evaluation of algorithms for processing massive data is a challenging research issue.
However, different algorithms can produce different or even conflicting evaluation performance, and this phenomenon has not been fully investigated.
The motivation of this paper aims to propose a solution scheme for the evaluation of clustering algorithms to reconcile different or even conflicting evaluation performance.
The goal of this research is to propose and develop a model, called decision-making support for evaluation of clustering algorithms (DMSECA), to evaluate clustering algorithms by merging expert wisdom in order to reconcile differences in their evaluation performance for information fusion during a complex decision-making process.
The proposed model is tested and verified by an experimental study using six clustering algorithms, nine external measures, and four MCDM methods on 20 UCI data sets, including a total of 18,310 instances and 313 attributes.
The proposed model can generate a list of algorithm priorities to produce an optimal ranking scheme, which can satisfy the decision preferences of all the participants.
The results indicate our developed model is an effective tool for selecting the most appropriate clustering algorithms for given data sets.
Furthermore, our proposed model can reconcile different or even conflicting evaluation performance to reach a group agreement in a complex decision-making environment.
American Psychological Association (APA)
Wu, Wenshuai& Xu, Zeshui& Kou, Gang& Shi, Yong. 2020. Decision-Making Support for the Evaluation of Clustering Algorithms Based on MCDM. Complexity،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1145693
Modern Language Association (MLA)
Wu, Wenshuai…[et al.]. Decision-Making Support for the Evaluation of Clustering Algorithms Based on MCDM. Complexity No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1145693
American Medical Association (AMA)
Wu, Wenshuai& Xu, Zeshui& Kou, Gang& Shi, Yong. Decision-Making Support for the Evaluation of Clustering Algorithms Based on MCDM. Complexity. 2020. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1145693
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1145693