A Fuzzy Co-Clustering Algorithm via Modularity Maximization
Joint Authors
Liu, Yongli
Chao, Hao
Chen, Jingli
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-29
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In this paper we propose a fuzzy co-clustering algorithm via modularity maximization, named MMFCC.
In its objective function, we use the modularity measure as the criterion for co-clustering object-feature matrices.
After converting into a constrained optimization problem, it is solved by an iterative alternative optimization procedure via modularity maximization.
This algorithm offers some advantages such as directly producing a block diagonal matrix and interpretable description of resulting co-clusters, automatically determining the appropriate number of final co-clusters.
The experimental studies on several benchmark datasets demonstrate that this algorithm can yield higher quality co-clusters than such competitors as some fuzzy co-clustering algorithms and crisp block-diagonal co-clustering algorithms, in terms of accuracy.
American Psychological Association (APA)
Liu, Yongli& Chen, Jingli& Chao, Hao. 2018. A Fuzzy Co-Clustering Algorithm via Modularity Maximization. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1207101
Modern Language Association (MLA)
Liu, Yongli…[et al.]. A Fuzzy Co-Clustering Algorithm via Modularity Maximization. Mathematical Problems in Engineering No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1207101
American Medical Association (AMA)
Liu, Yongli& Chen, Jingli& Chao, Hao. A Fuzzy Co-Clustering Algorithm via Modularity Maximization. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1207101
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1207101